This study investigates the employees’ perception of fairness in the performance appraisal system for academic staff of the General Sir Jhon Kotelawala Defence University.
Using Investigative Analytics to Speed New Drugs to MarketCognizant
Investigative analytics can help speed up clinical trials and bring new drugs to market faster. It does this by improving data quality monitoring during trials. Exploratory data analysis and inferential statistics are two types of analysis that can be used to identify data quality issues. Exploratory analysis uses techniques like outlier analysis and repeated value analysis to detect anomalies in the data. Inferential statistics helps confirm findings and identify which sites require auditing. Together these methods provide a more cost-effective way to ensure data integrity and compliance during clinical trials.
How to establish and evaluate clinical prediction models - StatsworkStats Statswork
A clinical prediction model can be used in various clinical contexts, including screening for asymptomatic illness, forecasting future events such as disease, and assisting doctors in their decision-making and health education. Despite the positive effects of clinical prediction models on practice, prediction modeling is a difficult process that necessitates meticulous statistical analysis and sound clinical judgments. Statswork offers statistical services as per the requirements of the customers. When you Order statistical Services at Statswork, we promise you the following always on Time, outstanding customer support, and High-quality Subject Matter Experts.
Read More With Us: https://bit.ly/3dxn32c
Why Statswork?
Plagiarism Free | Unlimited Support | Prompt Turnaround Times | Subject Matter Expertise | Experienced Bio-statisticians & Statisticians | Statistics across Methodologies | Wide Range of Tools & Technologies Supports | Tutoring Services | 24/7 Email Support | Recommended by Universities
Contact Us:
Website: www.statswork.com
Email: info@statswork.com
United Kingdom: 44-1143520021
India: 91-4448137070
WhatsApp: 91-8754446690
This document discusses the revised DEMATEL (Decision Making Trial and Evaluation Laboratory) method and provides examples of its application. It summarizes two examples where revised DEMATEL was used: (1) to analyze the causal relationships between seven criteria for improving hospital service quality based on patient surveys, and (2) to determine the weights of seven dimensions for evaluating innovation support systems in Taiwanese higher education based on expert surveys. It concludes that revised DEMATEL can produce results very similar or equal to the original DEMATEL method across all examples, except where the original method was infeasible. The closeness of the revised method's results depends on the epsilon value chosen.
An overview of fixed effects assumptions for meta analysis - PubricaPubrica
• The specific goals of meta-analysis include the estimation of an overall effect using different studies.
• The use of multiple studies provides a more robust test of the statistical use of the effect; and identification of variables affecting the estimated impact in different studies.
Continue Reading: https://bit.ly/35CHxm7
Reference: https://pubrica.com/services/research-services/meta-analysis/
Why Pubrica?
When you order our services, we promise you the following – Plagiarism free, always on Time, outstanding customer support, written to Standard, Unlimited Revisions support and High-quality Subject Matter Experts.
Contact us :
Web: https://pubrica.com/
Blog: https://pubrica.com/academy/
Email: sales@pubrica.com
WhatsApp : +91 9884350006
United Kingdom: +44- 74248 10299
The document discusses Cochrane Collaboration, which involves over 28,000 volunteers in over 100 countries who systematically review randomized controlled trials and other studies on health care interventions. The goal is to help people make informed health care decisions. Key principles include collaboration, avoiding bias, and ensuring quality and accessibility. Forest plots and meta-analyses are discussed as methods to combine results from multiple studies. Meta-analysis can identify overall effects, variables that explain differences between studies, and assess for publication bias. Single subject designs are also reviewed as a type of study that can be included in meta-analyses, though challenges exist in interpreting these designs.
A Framework for Statistical Simulation of Physiological Responses (SSPR).Waqas Tariq
The problem of variable selection from a large number of variables to predict certain important dependent variables has been of interest to both applied statisticians and other researchers in applied physiology. For this purpose, various statistical techniques have been developed. This framework embedded various statistical techniques of sampling and resampling and help in Statistical Simulation for Physiological Responses under different Environmental condition. The population generation and other statistical calculations are based on the inputs provided by the user as mean vector and covariance matrix and the data. This framework is developed in a way that it can work for the original data as well as for simulated data generated by the software. Approach: The mean vector and covariance matrix are sufficient statistics when the underlying distribution is multivariate normal. This framework uses these two inputs and is able to generate simulated multivariate normal population for any number of variables. The software changes the manual operation into a computer-based system to automate the study, provide efficiency, accuracy, timelessness, and economy. Result: A complete framework that can statistically simulate any type and any number of responses or variables. If the simulated data is analyzed using statistical techniques; the results of such analysis will be the same as that using the original data. If the data is missing for some of the variables, in that case the system will also help. Conclusion: The proposed system makes it possible to carry out the physiological studies and statistical calculations even if the actual data is not present.
This document discusses research design and data collection for statistical studies. It defines different study types including observational and interventional studies. Key aspects of research design covered include developing research questions, determining the appropriate study design, and selecting appropriate statistical tests. Specific study designs like randomized controlled trials and observational studies are described. The document also addresses topics like variables, sample size calculations, and representing data summaries.
Regression to the mean refers to the phenomenon where if a variable is extreme on its first measurement, it will tend to be closer to the average on a second measurement. This is because the first measurement is likely influenced in part by chance and the second measurement will regress back toward the mean. Failure to account for regression to the mean can lead to incorrect conclusions about the effectiveness of interventions or policies from pre-post comparisons. For example, the improvement seen in the worst performing schools after implementing new policies may be partly due to regression to the mean rather than the policies themselves. Regression to the mean is an important statistical concept to consider in designing experiments and interpreting data.
Using Investigative Analytics to Speed New Drugs to MarketCognizant
Investigative analytics can help speed up clinical trials and bring new drugs to market faster. It does this by improving data quality monitoring during trials. Exploratory data analysis and inferential statistics are two types of analysis that can be used to identify data quality issues. Exploratory analysis uses techniques like outlier analysis and repeated value analysis to detect anomalies in the data. Inferential statistics helps confirm findings and identify which sites require auditing. Together these methods provide a more cost-effective way to ensure data integrity and compliance during clinical trials.
How to establish and evaluate clinical prediction models - StatsworkStats Statswork
A clinical prediction model can be used in various clinical contexts, including screening for asymptomatic illness, forecasting future events such as disease, and assisting doctors in their decision-making and health education. Despite the positive effects of clinical prediction models on practice, prediction modeling is a difficult process that necessitates meticulous statistical analysis and sound clinical judgments. Statswork offers statistical services as per the requirements of the customers. When you Order statistical Services at Statswork, we promise you the following always on Time, outstanding customer support, and High-quality Subject Matter Experts.
Read More With Us: https://bit.ly/3dxn32c
Why Statswork?
Plagiarism Free | Unlimited Support | Prompt Turnaround Times | Subject Matter Expertise | Experienced Bio-statisticians & Statisticians | Statistics across Methodologies | Wide Range of Tools & Technologies Supports | Tutoring Services | 24/7 Email Support | Recommended by Universities
Contact Us:
Website: www.statswork.com
Email: info@statswork.com
United Kingdom: 44-1143520021
India: 91-4448137070
WhatsApp: 91-8754446690
This document discusses the revised DEMATEL (Decision Making Trial and Evaluation Laboratory) method and provides examples of its application. It summarizes two examples where revised DEMATEL was used: (1) to analyze the causal relationships between seven criteria for improving hospital service quality based on patient surveys, and (2) to determine the weights of seven dimensions for evaluating innovation support systems in Taiwanese higher education based on expert surveys. It concludes that revised DEMATEL can produce results very similar or equal to the original DEMATEL method across all examples, except where the original method was infeasible. The closeness of the revised method's results depends on the epsilon value chosen.
An overview of fixed effects assumptions for meta analysis - PubricaPubrica
• The specific goals of meta-analysis include the estimation of an overall effect using different studies.
• The use of multiple studies provides a more robust test of the statistical use of the effect; and identification of variables affecting the estimated impact in different studies.
Continue Reading: https://bit.ly/35CHxm7
Reference: https://pubrica.com/services/research-services/meta-analysis/
Why Pubrica?
When you order our services, we promise you the following – Plagiarism free, always on Time, outstanding customer support, written to Standard, Unlimited Revisions support and High-quality Subject Matter Experts.
Contact us :
Web: https://pubrica.com/
Blog: https://pubrica.com/academy/
Email: sales@pubrica.com
WhatsApp : +91 9884350006
United Kingdom: +44- 74248 10299
The document discusses Cochrane Collaboration, which involves over 28,000 volunteers in over 100 countries who systematically review randomized controlled trials and other studies on health care interventions. The goal is to help people make informed health care decisions. Key principles include collaboration, avoiding bias, and ensuring quality and accessibility. Forest plots and meta-analyses are discussed as methods to combine results from multiple studies. Meta-analysis can identify overall effects, variables that explain differences between studies, and assess for publication bias. Single subject designs are also reviewed as a type of study that can be included in meta-analyses, though challenges exist in interpreting these designs.
A Framework for Statistical Simulation of Physiological Responses (SSPR).Waqas Tariq
The problem of variable selection from a large number of variables to predict certain important dependent variables has been of interest to both applied statisticians and other researchers in applied physiology. For this purpose, various statistical techniques have been developed. This framework embedded various statistical techniques of sampling and resampling and help in Statistical Simulation for Physiological Responses under different Environmental condition. The population generation and other statistical calculations are based on the inputs provided by the user as mean vector and covariance matrix and the data. This framework is developed in a way that it can work for the original data as well as for simulated data generated by the software. Approach: The mean vector and covariance matrix are sufficient statistics when the underlying distribution is multivariate normal. This framework uses these two inputs and is able to generate simulated multivariate normal population for any number of variables. The software changes the manual operation into a computer-based system to automate the study, provide efficiency, accuracy, timelessness, and economy. Result: A complete framework that can statistically simulate any type and any number of responses or variables. If the simulated data is analyzed using statistical techniques; the results of such analysis will be the same as that using the original data. If the data is missing for some of the variables, in that case the system will also help. Conclusion: The proposed system makes it possible to carry out the physiological studies and statistical calculations even if the actual data is not present.
This document discusses research design and data collection for statistical studies. It defines different study types including observational and interventional studies. Key aspects of research design covered include developing research questions, determining the appropriate study design, and selecting appropriate statistical tests. Specific study designs like randomized controlled trials and observational studies are described. The document also addresses topics like variables, sample size calculations, and representing data summaries.
Regression to the mean refers to the phenomenon where if a variable is extreme on its first measurement, it will tend to be closer to the average on a second measurement. This is because the first measurement is likely influenced in part by chance and the second measurement will regress back toward the mean. Failure to account for regression to the mean can lead to incorrect conclusions about the effectiveness of interventions or policies from pre-post comparisons. For example, the improvement seen in the worst performing schools after implementing new policies may be partly due to regression to the mean rather than the policies themselves. Regression to the mean is an important statistical concept to consider in designing experiments and interpreting data.
Download Link > https://ertekprojects.com/gurdal-ertek-publications/blog/scoring-and-predicting-risk-preferences/
This study presents amethodology to determine risk scores of individ-uals, for a given financial risk preference survey. To this end, we use a regression-based iterative algorithm to determine the weights for survey questions in the scoring process. Next, we generate classification models to classify individuals into risk-averse and risk-seeking categories, using a subset of survey questions. We illustrate the methodology through a sample survey with 656 respondents. We find that the demographic (indirect) questions can be almost as successful as risk-related (direct) questions in predicting risk preference classes of respon-dents. Using a decision-tree based classification model, we discuss how one can generate actionable business rules based on the findings.
Research method ch14 selected research papersUuganaa Baatar
This document summarizes a research study that evaluated a mobile phone-based diet game for weight control. The study:
1. Developed a mobile phone app called SmartDiet to track nutrition intake and include games to help with weight control.
2. Aimed to evaluate the effectiveness of the app in helping obese patients manage their weight.
3. Collected data on patients' nutrition intake and weight changes over time to analyze the impact of using the app.
Classification Scoring for Cleaning Inconsistent Survey DataCSCJournals
Data engineers are often asked to detect and resolve inconsistencies within data sets. For some data sources with problems, there is no option to ask for corrections or updates, and the processing steps must do their best with the values in hand. Such circumstances arise in processing survey data, in constructing knowledge bases or data warehouses [1] and in using some public or open data sets.
The goal of data cleaning, sometimes called data editing or integrity checking, is to improve the accuracy of each data record and by extension the quality of the data set as a whole. Generally, this is accomplished through deterministic processes that recode specific data points according to static rules based entirely on data from within the individual record. This traditional method works well for many purposes. However, when high levels of inconsistency exist within an individual respondent's data, classification scoring may provide better results.
Classification scoring is a two-stage process that makes use of information from more than the individual data record. In the first stage, population data is used to define a model, and in the second stage the model is applied to the individual record. The author and colleagues turned to a classification scoring method to resolve inconsistencies in a key value from a recent health survey. Drawing records from a pool of about 11,000 survey respondents for use in training, we defined a model and used it to classify the vital status of the survey subject, since in the case of proxy surveys, the subject of the study may be a different person from the respondent. The scoring model was tested on the next several months' receipts and then applied on a flow basis during the remainder of data collection to the scanned and interpreted forms for a total of 18,841 unique survey subjects. Classification results were confirmed through external means to further validate the approach. This paper provides methodology and algorithmic details and suggests when this type of cleaning process may be useful.
Data inaccuracies were identified and then classified
as either clinically significant or not significant.
Data inaccuracies were observed in 53.33% of articles
ranging from 3.33% to 45% based on the IMRAD format
sections. The Results section showed the highest discrepancies
(45%) although these were deemed to be mostly
not significant clinically except in one. The two most
common discrepancies were mismatched numbers or
percentages (11.67%) and numerical data or calculations
found in structured abstracts but not mentioned in the
full text (40%). There was no significant relationship
between journals and the presence of discrepancies
(Fisher’s exact p value =0.3405). Although we found a
high percentage of inaccuracy between structured
abstracts and full-text articles, these were not significant
clinically.
Design of experiments is the most common Research design will wide reliability. It is mostly applicable in scientific lab type of research. This method is not applicable for descriptive research.
It involves both qualitative and quantitative data sets. The researchers can manipulate, control, replicate and randomize the experimental variables.
There are several types of experimental design depending on the selection of control, test and standard groups and their experimental setting.
The slides also show the guidelines regarding design of research proposal, Literature survey and important ethics in research. Guiding protocol to prepare a research and review article is also discussed.
Prioritization of various dimensions of service quality in hospitality industryIAEME Publication
This document discusses prioritizing dimensions of service quality in the hospitality industry using multiple regression analysis. It reviews literature on different weighting methods and chooses multiple regression analysis as most suitable. The study evaluates the relative importance of the five SERVQUAL dimensions - tangibles, reliability, responsiveness, assurance, and empathy. Primary data is collected from hotels in Uttarakhand, India to perform the multiple regression analysis and prioritize the dimensions. The results provide a way to rank the service quality dimensions specifically for the hospitality industry context.
This document discusses investigating heterogeneity in meta-analyses through subgroup analysis and meta-regression. It outlines when and how to use these techniques to explore reasons for variability in study results. Key challenges include having enough studies, selecting explanatory variables carefully to avoid false positives, and accounting for confounding and aggregation bias in study-level data. Meta-regression allows for random effects but interpretation requires caution given observational relationships between study characteristics and effects.
The use of Prediction Intervals in Meta-AnalysisNikesh Patel
The document discusses the use of prediction intervals in meta-analysis. It describes how meta-analysis combines results from multiple studies and can report a summary estimate using either a fixed-effect or random-effects model. While random-effects models account for heterogeneity, they typically only report confidence intervals which do not reflect the full uncertainty. Prediction intervals provide a range that future study results are likely to fall within by incorporating heterogeneity. The author examines existing meta-analyses to see how prediction intervals impact results and applies them to meta-epidemiological studies.
This document discusses various research designs used in experimental research, including pre-experimental, true experimental, quasi-experimental, and statistical designs. Pre-experimental designs lack random assignment, while true experiments use random assignment to treatment and control groups. Quasi-experiments provide some control but no random assignment. Statistical designs allow statistical analysis and control of external variables through randomization and matching. The document outlines different designs and their strengths and weaknesses in establishing internal and external validity.
This chapter discusses causal research design and experimentation. It begins with an overview of causality and the conditions required for causality, including concomitant variation and time order. It then defines key concepts in experimentation like independent, dependent, and extraneous variables. The chapter classifies different types of experimental designs, from pre-experimental to true experiments to quasi-experiments. It covers validity, controlling extraneous variables, and statistical designs. It also discusses limitations of experimentation and strategies for test marketing.
Imran rizvi statistics in meta analysisImran Rizvi
This document discusses statistics used in meta-analyses. It explains that meta-analyses statistically combine results from multiple studies on a topic. Effect measures are calculated for individual studies and then combined to find an overall effect. For dichotomous outcomes, common effect measures are risk ratio, odds ratio, and absolute risk reduction. Random effects models account for heterogeneity between studies, while fixed effect models assume one true effect. Forest plots visually display individual study results and the overall effect, allowing readers to assess consistency and precision.
This document discusses causal-comparative research, which investigates potential causes of existing differences between groups. Key points include: causal-comparative research is a form of associative research that examines nonexperimental group differences; threats to internal validity like subject characteristics must be evaluated; and data analysis may involve t-tests, ANCOVAs, or crossbreak tables to compare group means or associations between categorical variables.
ABSTRACT : This paper critically examined a broad view of Structural Equation Model (SEM) with a view
of pointing out direction on how researchers can employ this model to future researches, with specific focus on
several traditional multivariate procedures like factor analysis, discriminant analysis, path analysis. This study
employed a descriptive survey and historical research design. Data was computed viaDescriptive Statistics,
Correlation Coefficient, Reliability. The study concluded that Novice researchers must take care of assumptions
and concepts of Structure Equation Modeling, while building a model to check the proposed hypothesis. SEM is
more or less an evolving technique in the research, which is expanding to new fields. Moreover, it is providing
new insights to researchers for conducting longitudinal investigations.
.
This document outlines the concepts and methods of multiple-treatments meta-analysis (MTM). MTM allows for the simultaneous comparison of multiple interventions for a condition by combining both direct and indirect evidence from randomized controlled trials. Key advantages of MTM include the ability to rank treatments, comprehensively use all available data, and compare interventions not directly compared in trials. The document discusses MTM approaches using frequentist meta-regression and Bayesian statistics.
This document provides an overview of operations research (OR). It begins with the history and origins of OR, noting it emerged from efforts during WWII and expanded to business/industry post-war. Definitions of OR are presented focusing on using research to identify and solve program problems. The purpose, scope, uses and potential issues of OR are described. Finally, the document outlines the process of OR including planning, implementation, and follow through.
Drug Review Sentiment Analysis using Boosting Algorithmsijtsrd
Sentiment Analysis of the Reviews is important to understand the positive or negative effect of some process using their reviews after the experience. In the study the sentiment analysis of the reviews of drugs given by the patients after the usage using the boosting algorithms in machine learning. The Dataset used, provides patient reviews on some specific drugs along with the conditions the patient is suffering from and a 10 star patient rating reflecting the patient satisfaction. Exploratory Data Analysis is carried out to get more insight and engineer features. Preprocessing is done to get the data ready. The sentiment of the review is given according to the rating of the drugs. To classify the reviews as positive or negative three Classification models are trained LightGBM, XGBoost, and CatBoost and the feature importance is plotted. The result shows that LGBM is the best performing Boosting algorithm with an accuracy of 88.89 . Sumit Mishra "Drug Review Sentiment Analysis using Boosting Algorithms" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd42429.pdf Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/42429/drug-review-sentiment-analysis-using-boosting-algorithms/sumit-mishra
The document defines and discusses various types of validity and reliability in research experiments and measurements. It summarizes the key threats to internal and external validity in experiments. It also defines correlation research and distinguishes between explanatory and predictive research designs. Finally, it defines ethnographic research, when it should be used, and outlines the five key steps in conducting an ethnographic study.
In this ppt the viewer will able to know about Types of Experimental Design. During the research design what kind of experimental design is applicable? Why experimental design needed in experimental research. Experimental research is research conducted with a scientific approach using two sets of variables. The first set acts as a constant, which you use to measure the differences of the second set. (Example: Temperature & Time in reactor)
Portion explained:
1. Definition of Experimental research
2. Situations to conduct Experimental Research
3. Types of experimental research design
4. Pre-experimental research design
5. True experimental research design
6. Quasi-experimental research design
7. Advantages of experimental research
Reliability Analysis Of Refined Model With 25 Items And 5...Jessica Myers
This study examines the psychological factors that motivate different expressions of prejudice in modern society. The researchers analyzed both covert and overt manifestations of bias using a scale to measure the motivation to express prejudice. Through four survey studies, the researchers aimed to distinguish between deliberate and subconscious prejudice by assessing the influence of social norms as well as internal and external forces. The results indicated that prejudice is not solely dictated by social norms, but also other psychological factors, helping to explain prejudice at both the conscious and unconscious levels.
RTI International used a technique called meta-evaluation to analyze data from 108 health care innovation projects funded by the Center for Medicare and Medicaid Innovation. Meta-evaluation combines qualitative and quantitative data using methods inspired by meta-analysis. It systematically collects data on each project's characteristics and outcomes to identify which types of innovations were most effective and understand why some projects had more success than others. RTI developed an interactive online dashboard to help policymakers visualize the data and explore relationships between different project features and their impact on outcomes like costs and hospital admissions. The goal is to inform decisions about scaling up or modifying health care delivery and payment models.
Download Link > https://ertekprojects.com/gurdal-ertek-publications/blog/scoring-and-predicting-risk-preferences/
This study presents amethodology to determine risk scores of individ-uals, for a given financial risk preference survey. To this end, we use a regression-based iterative algorithm to determine the weights for survey questions in the scoring process. Next, we generate classification models to classify individuals into risk-averse and risk-seeking categories, using a subset of survey questions. We illustrate the methodology through a sample survey with 656 respondents. We find that the demographic (indirect) questions can be almost as successful as risk-related (direct) questions in predicting risk preference classes of respon-dents. Using a decision-tree based classification model, we discuss how one can generate actionable business rules based on the findings.
Research method ch14 selected research papersUuganaa Baatar
This document summarizes a research study that evaluated a mobile phone-based diet game for weight control. The study:
1. Developed a mobile phone app called SmartDiet to track nutrition intake and include games to help with weight control.
2. Aimed to evaluate the effectiveness of the app in helping obese patients manage their weight.
3. Collected data on patients' nutrition intake and weight changes over time to analyze the impact of using the app.
Classification Scoring for Cleaning Inconsistent Survey DataCSCJournals
Data engineers are often asked to detect and resolve inconsistencies within data sets. For some data sources with problems, there is no option to ask for corrections or updates, and the processing steps must do their best with the values in hand. Such circumstances arise in processing survey data, in constructing knowledge bases or data warehouses [1] and in using some public or open data sets.
The goal of data cleaning, sometimes called data editing or integrity checking, is to improve the accuracy of each data record and by extension the quality of the data set as a whole. Generally, this is accomplished through deterministic processes that recode specific data points according to static rules based entirely on data from within the individual record. This traditional method works well for many purposes. However, when high levels of inconsistency exist within an individual respondent's data, classification scoring may provide better results.
Classification scoring is a two-stage process that makes use of information from more than the individual data record. In the first stage, population data is used to define a model, and in the second stage the model is applied to the individual record. The author and colleagues turned to a classification scoring method to resolve inconsistencies in a key value from a recent health survey. Drawing records from a pool of about 11,000 survey respondents for use in training, we defined a model and used it to classify the vital status of the survey subject, since in the case of proxy surveys, the subject of the study may be a different person from the respondent. The scoring model was tested on the next several months' receipts and then applied on a flow basis during the remainder of data collection to the scanned and interpreted forms for a total of 18,841 unique survey subjects. Classification results were confirmed through external means to further validate the approach. This paper provides methodology and algorithmic details and suggests when this type of cleaning process may be useful.
Data inaccuracies were identified and then classified
as either clinically significant or not significant.
Data inaccuracies were observed in 53.33% of articles
ranging from 3.33% to 45% based on the IMRAD format
sections. The Results section showed the highest discrepancies
(45%) although these were deemed to be mostly
not significant clinically except in one. The two most
common discrepancies were mismatched numbers or
percentages (11.67%) and numerical data or calculations
found in structured abstracts but not mentioned in the
full text (40%). There was no significant relationship
between journals and the presence of discrepancies
(Fisher’s exact p value =0.3405). Although we found a
high percentage of inaccuracy between structured
abstracts and full-text articles, these were not significant
clinically.
Design of experiments is the most common Research design will wide reliability. It is mostly applicable in scientific lab type of research. This method is not applicable for descriptive research.
It involves both qualitative and quantitative data sets. The researchers can manipulate, control, replicate and randomize the experimental variables.
There are several types of experimental design depending on the selection of control, test and standard groups and their experimental setting.
The slides also show the guidelines regarding design of research proposal, Literature survey and important ethics in research. Guiding protocol to prepare a research and review article is also discussed.
Prioritization of various dimensions of service quality in hospitality industryIAEME Publication
This document discusses prioritizing dimensions of service quality in the hospitality industry using multiple regression analysis. It reviews literature on different weighting methods and chooses multiple regression analysis as most suitable. The study evaluates the relative importance of the five SERVQUAL dimensions - tangibles, reliability, responsiveness, assurance, and empathy. Primary data is collected from hotels in Uttarakhand, India to perform the multiple regression analysis and prioritize the dimensions. The results provide a way to rank the service quality dimensions specifically for the hospitality industry context.
This document discusses investigating heterogeneity in meta-analyses through subgroup analysis and meta-regression. It outlines when and how to use these techniques to explore reasons for variability in study results. Key challenges include having enough studies, selecting explanatory variables carefully to avoid false positives, and accounting for confounding and aggregation bias in study-level data. Meta-regression allows for random effects but interpretation requires caution given observational relationships between study characteristics and effects.
The use of Prediction Intervals in Meta-AnalysisNikesh Patel
The document discusses the use of prediction intervals in meta-analysis. It describes how meta-analysis combines results from multiple studies and can report a summary estimate using either a fixed-effect or random-effects model. While random-effects models account for heterogeneity, they typically only report confidence intervals which do not reflect the full uncertainty. Prediction intervals provide a range that future study results are likely to fall within by incorporating heterogeneity. The author examines existing meta-analyses to see how prediction intervals impact results and applies them to meta-epidemiological studies.
This document discusses various research designs used in experimental research, including pre-experimental, true experimental, quasi-experimental, and statistical designs. Pre-experimental designs lack random assignment, while true experiments use random assignment to treatment and control groups. Quasi-experiments provide some control but no random assignment. Statistical designs allow statistical analysis and control of external variables through randomization and matching. The document outlines different designs and their strengths and weaknesses in establishing internal and external validity.
This chapter discusses causal research design and experimentation. It begins with an overview of causality and the conditions required for causality, including concomitant variation and time order. It then defines key concepts in experimentation like independent, dependent, and extraneous variables. The chapter classifies different types of experimental designs, from pre-experimental to true experiments to quasi-experiments. It covers validity, controlling extraneous variables, and statistical designs. It also discusses limitations of experimentation and strategies for test marketing.
Imran rizvi statistics in meta analysisImran Rizvi
This document discusses statistics used in meta-analyses. It explains that meta-analyses statistically combine results from multiple studies on a topic. Effect measures are calculated for individual studies and then combined to find an overall effect. For dichotomous outcomes, common effect measures are risk ratio, odds ratio, and absolute risk reduction. Random effects models account for heterogeneity between studies, while fixed effect models assume one true effect. Forest plots visually display individual study results and the overall effect, allowing readers to assess consistency and precision.
This document discusses causal-comparative research, which investigates potential causes of existing differences between groups. Key points include: causal-comparative research is a form of associative research that examines nonexperimental group differences; threats to internal validity like subject characteristics must be evaluated; and data analysis may involve t-tests, ANCOVAs, or crossbreak tables to compare group means or associations between categorical variables.
ABSTRACT : This paper critically examined a broad view of Structural Equation Model (SEM) with a view
of pointing out direction on how researchers can employ this model to future researches, with specific focus on
several traditional multivariate procedures like factor analysis, discriminant analysis, path analysis. This study
employed a descriptive survey and historical research design. Data was computed viaDescriptive Statistics,
Correlation Coefficient, Reliability. The study concluded that Novice researchers must take care of assumptions
and concepts of Structure Equation Modeling, while building a model to check the proposed hypothesis. SEM is
more or less an evolving technique in the research, which is expanding to new fields. Moreover, it is providing
new insights to researchers for conducting longitudinal investigations.
.
This document outlines the concepts and methods of multiple-treatments meta-analysis (MTM). MTM allows for the simultaneous comparison of multiple interventions for a condition by combining both direct and indirect evidence from randomized controlled trials. Key advantages of MTM include the ability to rank treatments, comprehensively use all available data, and compare interventions not directly compared in trials. The document discusses MTM approaches using frequentist meta-regression and Bayesian statistics.
This document provides an overview of operations research (OR). It begins with the history and origins of OR, noting it emerged from efforts during WWII and expanded to business/industry post-war. Definitions of OR are presented focusing on using research to identify and solve program problems. The purpose, scope, uses and potential issues of OR are described. Finally, the document outlines the process of OR including planning, implementation, and follow through.
Drug Review Sentiment Analysis using Boosting Algorithmsijtsrd
Sentiment Analysis of the Reviews is important to understand the positive or negative effect of some process using their reviews after the experience. In the study the sentiment analysis of the reviews of drugs given by the patients after the usage using the boosting algorithms in machine learning. The Dataset used, provides patient reviews on some specific drugs along with the conditions the patient is suffering from and a 10 star patient rating reflecting the patient satisfaction. Exploratory Data Analysis is carried out to get more insight and engineer features. Preprocessing is done to get the data ready. The sentiment of the review is given according to the rating of the drugs. To classify the reviews as positive or negative three Classification models are trained LightGBM, XGBoost, and CatBoost and the feature importance is plotted. The result shows that LGBM is the best performing Boosting algorithm with an accuracy of 88.89 . Sumit Mishra "Drug Review Sentiment Analysis using Boosting Algorithms" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd42429.pdf Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/42429/drug-review-sentiment-analysis-using-boosting-algorithms/sumit-mishra
The document defines and discusses various types of validity and reliability in research experiments and measurements. It summarizes the key threats to internal and external validity in experiments. It also defines correlation research and distinguishes between explanatory and predictive research designs. Finally, it defines ethnographic research, when it should be used, and outlines the five key steps in conducting an ethnographic study.
In this ppt the viewer will able to know about Types of Experimental Design. During the research design what kind of experimental design is applicable? Why experimental design needed in experimental research. Experimental research is research conducted with a scientific approach using two sets of variables. The first set acts as a constant, which you use to measure the differences of the second set. (Example: Temperature & Time in reactor)
Portion explained:
1. Definition of Experimental research
2. Situations to conduct Experimental Research
3. Types of experimental research design
4. Pre-experimental research design
5. True experimental research design
6. Quasi-experimental research design
7. Advantages of experimental research
Reliability Analysis Of Refined Model With 25 Items And 5...Jessica Myers
This study examines the psychological factors that motivate different expressions of prejudice in modern society. The researchers analyzed both covert and overt manifestations of bias using a scale to measure the motivation to express prejudice. Through four survey studies, the researchers aimed to distinguish between deliberate and subconscious prejudice by assessing the influence of social norms as well as internal and external forces. The results indicated that prejudice is not solely dictated by social norms, but also other psychological factors, helping to explain prejudice at both the conscious and unconscious levels.
RTI International used a technique called meta-evaluation to analyze data from 108 health care innovation projects funded by the Center for Medicare and Medicaid Innovation. Meta-evaluation combines qualitative and quantitative data using methods inspired by meta-analysis. It systematically collects data on each project's characteristics and outcomes to identify which types of innovations were most effective and understand why some projects had more success than others. RTI developed an interactive online dashboard to help policymakers visualize the data and explore relationships between different project features and their impact on outcomes like costs and hospital admissions. The goal is to inform decisions about scaling up or modifying health care delivery and payment models.
Methods Of Program Evaluation. Evaluation Research Is OfferedJennifer Wood
This document discusses different approaches to evaluation research and program evaluation. It provides examples of different types of evaluation research, such as problem analysis, evidence-based policy, and evidence generation. It also discusses publication bias in medical informatics evaluation research and evaluates the training evaluation process for a dinner event. Key aspects of performance evaluations and the challenges associated with the performance evaluation process are outlined as well. Different participant-oriented approaches to evaluation like participatory evaluation, developmental evaluation, and empowerment evaluation are also presented.
This document discusses reliability and validity, which are two important concepts for evaluating data collection methods in human services. Reliability refers to the consistency and dependability of measurements or assessments, and there are different types of reliability such as inter-rater reliability and test-retest reliability. Validity refers to whether a measurement or assessment accurately measures what it claims to measure. The document emphasizes that reliability and validity are crucial for human services to obtain accurate information through effective data collection methods when evaluating programs and services.
Determinants of employees performance in ready made garments rm gs sector in...rakib41
This study aimed to determine the factors that influence employees' performance in the ready-made garments sector in Chittagong, Bangladesh. The researchers conducted surveys of 100 employees from 20 garment companies. They found that individual-related factors, job-related factors, and organizational-related factors all had a strong positive correlation with employees' performance. Path analysis showed that organizational-related factors had the strongest direct effect on performance, followed by individual-related factors. The study suggests focusing on organizational factors like culture, communication, and supervisor support to enhance employees' performance.
Analysis of Performance Appraisal Systems on Employee Job Productivity in Pub...inventionjournals
Universities appraisal system is meant to enhance the performance of employees by integrating an individual’s goal with those of the organization. Despite the Universities Management having an appraisal system, performance in public universities in the country remains relatively poor. The purpose of the study was to analyze performance appraisal systems on employee job productivity in public universities. The main objective of the study was to determine the effect of self-assessment on the performance of employees in Public Universities. The research study was carried out in four universities namely Masinde Muliro University of Science and Technology, Maseno, Moi and Jaramogi Oginga Odinga University of Science and Technology. Data collection instruments used was mainly questionnaire. Both content and construct reliability was carried out through engagement of experts in preparing the questionnaire. Piloting was done in Laikipia University College, though the results were not used in the study. To ensure that the instrument is reliable, a Cronbach’s Alpha of Coefficient of 0.876, was attained, which is far way above the recommended 0.7 in social sciences. The study employed descriptive survey research design. The target population consisted of 11,296 employees and 4 Registrars in charge of Administration. Purposive sampling was used to select the four universities and four registrars. Data analysis was done using the statistical Package for Social Science (Version 20). Both descriptive and inferential statistics were used in data analysis. The results were presented in form of tables, charts and cross tabulations. From the findings, self-assessment was an important section in performance appraisal as it contributed to improvement in employee job productivity. The findings will contribute to the pool of knowledge in the field of Human Resource Management and will form the basis of reference by interested parties in future. The management of public universities will use the findings of this study to guide them in performance management. Furthermore, the findings will be a source of reference for academicians who intend to carry out studies in relation to the subject of performance appraisal systems.
Evaluation of employee performance is an important element in enhancing the quality of the work and
improves employees’ motivation to perform well. It also presents a basis for upgrading and enhancing of
an organization. Periodical employees’ performance evaluation in an organization assists management to
recognize its strengths and weaknesses.
This paper presents a design and implementation of a performance appraisal system using the fuzzy logic.
In addition to the normal process of performance evaluation modules, the system contains step by step
inference engine processes. These processes demonstrate several calculation details in relations
composition and aggregation methods such as min operator, algebraic product, sup-min and sup-product.
The system has foundation to add-on analysis module to analyze and report the final result using various
similarity measures. MS Access database was used to maintain the data, build the inference logic and
develop all setting user interfaces.
This study examined the formative impact of general practice appraisals through a questionnaire given to GPs who had undergone appraisal at a primary care trust in Wessex, UK. The study found that appraisals increased GPs' confidence, improved patient care, and contributed to delayed retirement. Appraisals helped identify clear and achievable learning goals in areas like clinical skills, practice management, and personal development. Regular appraiser training and experience with multiple appraisals helped increase GPs' comfort with the process. The study provides insight into the educational benefits of appraisals when separated from revalidation requirements.
Running head evaluation tool1evaluation tool6Evaluation Tool.docxcowinhelen
Running head: evaluation tool 1
evaluation tool 6Evaluation Tool
Name
University
Class
Date
Evaluation Tool
Conducting the literature review and the evaluation methodology provided an insight into PICO question (Does implementing a new unified acute and ambulatory EHR (Electronic Health Record) system in the hospital, compared to when they are not used, improve the health care quality for the patients through documentation), and obtaining important information about what needs to be considered in a research project, particularly regarding research tool. The research should consider a tool that proves to be reliable and valid. The researcher should want to know if the tool is accurate and measuring what it is intended to measure (Penfold et al., 2011). Picking the wrong tool for research would result in an incomplete result, hence problem with the evidence. Thus, subsequent researchers may not want to use the flawed methodology to conduct their research. The purpose of this paper is to describe the selected evaluation tool for the project with a rationale, to summarize the criteria used in defining evaluation success, and to develop the assessment plan.Describing the Evaluation Tool Selected for the Evaluation Project
The chosen tool for evaluation is the “Electronic Health Record End User Survey” (AHRQ, n.d.). The tool is a questionnaire that focuses on the usability of an EHR. The questionnaire is designed for the clinical staff in the ambulatory setting to evaluate the usability of an electronic health record in ambulatory care. The aim of the assessment tool is to measure the appropriateness of ambulatory care after the implementation of clinical documentation. The device involves various types of a survey that incorporate many stakeholders who ensure that the hospital adopts new technology relating to the improvement of health care within the hospital. The tool is associated with a survey tool for assessing the EHR implementation based on development initiatives guide. The EHR End User Survey measures the effectiveness realized in the hospital setup through documentation as compared to using the old system of documentation. Based on the developed PICO question that aims at evaluating the benefits that subsume the overtaken documentation. The evaluation tool captures various hospital domains including the end users feedback regarding training and competency, usefulness, usability, infrastructure, and the user support. The tool involves the validation efforts based on needs assessment, the pilot study and the analysis of the nurse respondents. The End User Survey tool based on the EHR provides questionnaire type of review where the clinical staff answer the asked questions focusing on the current state assessment and usability within the hospital. The remote documentation applicable to the new unified ambulatory system makes it easier and efficient since it increases the number o ...
Face Construct And Criterion-Related Validity EssayDeb Birch
The document discusses validity and reliability as they relate to psychological assessment tools. It describes different types of validity, including face validity, construct validity, and criterion-related validity. Face validity assesses whether a test appears to measure what it intends to, construct validity examines how well a test measures a theoretical construct, and criterion-related validity determines whether test scores correlate with a criterion measure. The document also discusses reliability and notes that internal consistency and test-retest reliability are two important reliability considerations. Internal consistency ensures items on a test consistently measure the same construct, while test-retest reliability examines consistency of scores over time.
Topic- Contemporary business issueName of the Student .docxjuliennehar
This document provides a summary of 15 sources that discuss various topics related to employee performance monitoring. The sources examine the psychological implications of electronic performance monitoring, the impact of performance management systems on employee satisfaction, and how consistency and leadership can affect individual innovation. Methods discussed include surveys, interviews, and analyzing multiple data sets. Overall, the sources suggest that while performance monitoring can potentially improve productivity, it also risks negatively impacting employees and requires diverse, considerate approaches to maximize benefits and minimize adverse reactions.
Pre Assessment Quantitative And Qualitative Data EssayTiffany Sandoval
Here are the key factors to consider when deciding between quantitative and qualitative data:
- Sample size - Qualitative data uses smaller samples to gain an in-depth understanding of each case, while quantitative data relies on larger samples for generalizability.
- Data type - Quantitative data is numerical and can be easily grouped, compared, and analyzed statistically. Qualitative data includes text, images, and narratives that require different analysis methods.
- Research questions - Qualitative research is best for exploring a problem or generating hypotheses, while quantitative research tests hypotheses and measures outcomes.
- Resources - Qualitative data collection and analysis takes more time and resources per subject compared to quantitative methods with standardized instruments.
- Validity - It can
Assignment DescriptionA reputable hospital has high quality .docxluearsome
Assignment Description
A reputable hospital has high quality ratings from patient satisfaction surveys but is still losing market share. For many years, health care organizations, as well as traditional businesses, have been frustrated that high customer satisfaction scores do not necessarily lead to higher levels of profitability or sales.
Prepare a report examining this phenomenon that address the following elements:
Evaluate and explain inconsistency between customer satisfaction scores and profitability and why it tends to exist in health care organizations.
Apply the statistical procedures discussed in class to support (or refute) the inconsistency.
Assess price vs. quality of services as well as the impact of insurance or managed care contracts on a hospital's market share, regardless of patient satisfaction levels.
Explain how you could use high patient satisfaction results to your advantage when negotiating a new managed care contract for the hospital. Discuss ethical issues involved when presenting results.
Discuss how qualitative and quantitative data can be used to help this hospital improve market share.
The body of the resultant report should be 5–7 pages and include at least 5 relevant peer-reviewed academic or professional references published within the past 5 years.
Library Resources:
Statistical Analysis 1 Below is a list of articles and summary descriptions on effective communication in health care. Click here to use the online library to search for the complete articles. Article 1 The increased use of meta-analysis in systematic reviews of health care interventions has highlighted several types of bias that can arise during the completion of a randomized controlled trial. Study publication bias and outcome reporting bias have been recognized as potential threats to the validity of meta-analysis and can make the readily available evidence unreliable for decision making. This update reviews and summarizes the evidence from cohort studies that have assessed study publication bias or outcome reporting bias in randomized controlled trials. Twenty studies were eligible, of which four were newly identified in this update. Only two followed the cohort all the way through from protocol approval to information regarding the publication of outcomes. Fifteen of the studies investigated study publication bias and five investigated outcome reporting bias. Three studies have found that statistically significant outcomes had higher odds of being fully reported as compared to nonsignificant outcomes (range of odds ratios: 2.2–4.7). In comparing trial publications to protocols, it was found that 40–62% of studies had at least one primary outcome that was changed, introduced, or omitted. It was decided not to undertake meta-analysis because of the differences between studies. This update does not change the conclusions of the review in which 16 studies were included. Direct empirical evidence for the existence of study publica ...
This document summarizes a study that assessed the relationship between employee productivity, capacity building, and performance in cooperative banks in Nagpur, India. The study used questionnaires distributed to human resource managers, bank managers, and supervisors across all cooperative banks in the district. Statistical analysis found a positive relationship between capacity building activities like training, employee productivity, customer satisfaction, and bank performance. Specifically, improvements in employee skills, motivation, and satisfaction through capacity building initiatives led to increased customer satisfaction and loyalty, which in turn improved financial performance metrics for the banks. The study provides evidence that investing in employees through training and development has tangible benefits for organizational success.
FOCUSING YOUR RESEARCH EFFORTS Planning Your Research ShainaBoling829
FOCUSING YOUR RESEARCH
EFFORTS
Planning Your Research Project Chapter Four
What is the Research Design?
The research design is the general strategy that
provides the overall structures for the procedures
used in the research project. It is the planning
guide.
The Basic Format of the Research
Design
The question
The question converted to a research problem
A temporary hypothesis
Literature search
Data collection
Organization of the data
Analysis of the data
Interpretation of the data
The data either support or do not support the
hypothesis
Planning vs. Methodology
The general approach
to planning research is
similar across all
disciplines
The strategies used to
collect and analyze
data may be specific
to a particular
academic discipline
Research Planning Research Methodology
General Criteria for a Research Project
Universality (can be carried out by any competent
researcher)
Replication
Control (important for replication)
Measurement
The Nature and Role of Data
Data (plural) ‘data are’
Data ARE NOT absolute reality
Data are transient and ever changing
Primary Data are closest to truth
No researcher can glimpse ABSOLUTE TRUTH
Criteria for the Admissibility of Data
Any research effort should be replicable
Restrictions we identify are the criteria for the
admissibility of data
Standardize the data
Planning for Data Collection
What data are needed?
Where is the data located?
How will data be obtained?
How will data be interpreted?
Defining Measurement
Measurement is limiting the data of any
phenomenon – substantial or insubstantial – so that
those data may be interpreted and ultimately
compared to a particular qualitative or quantitative
standard
Measurement is ultimately a comparison: a think or
concept measured against a point of limitation
Types of Measurement Scales
Nominal Scales
Ordinal Scales
Interval Scales
Ratio Scales
Nominal Scales
A nominal scale limits the data
Nominal measurement is simplistic, but it does divide
data into discrete categories that can be compared
to one another.
Only a few statistical procedures are appropriate
for analyzing nominal data (a) mode, (b)
percentage, and (c) chi-square test
Ordinal Scales
Ordinal scales allow us to rank-order data
In addition to using statistics we can use with
nominal data, we can also use statistical procedures
to determine (a) the median, (b) the percentile rank,
and (c) Spearman’s rank order correlation
Interval Scales
An interval scale is characterized by two features:
(a) it has equal units of measurement, and (b) its
zero point has been established arbitrarily
Interval scales allow statistical analyses that are not
possible with nominal and ordinal data
Because an interval scale reflects equal distances ...
Decentralization Analysis of Decision Making and Performance of Accounting Co...IOSR Journals
This document summarizes a study that analyzed the effect of decentralization of decision-making and the use of accounting control systems on organizational performance. The study used a sample of 53 managers from a university in Indonesia. Statistical tests found that decentralization of decision-making and the use of accounting controls together explained 27.5% of the variation in organizational performance. Individual tests found that decentralization of decision-making had a slightly stronger influence on performance than accounting controls. The study concluded that decentralizing decision-making and using accounting controls can improve organizational performance.
In educational research, Research errors may be grouped under some headings:
1. Sampling errors
2. Measurement errors
3. Statistical errors
4. Interpretation errors
along with suggestions to reduce them
EFFECTS OF REWARD SYSTEMS ON EMPLOYEE PRODUCTIVITY IN CATHOLIC UNIVERSITY OF ...paperpublications3
Abstract:The main objective of this study was to assess the effects of reward systems on employee productivity in The Catholic University of Eastern Africa, Kenya. It further sought to determine the factors which increase employee motivation to better performance and critically evaluate and focus on the effects of reward systems on employee productivity. Purposive sampling was used to sample 80 respondents from all cadres of staff. Data was collected through self-administered questionnaires on a delivery and collection basis to the respondents. Regression technique was used to analyze the data. The data was analyzed using Statistical Package for Social Scientists (SPSS). The findings of this study revealed that different respondents had different motivational preferences but majority of the Institution’s staff was more exposed to the use of non-financial rewards such as recognition, training, opportunities to handle greater responsibilities, employee promotion and participation in key decision making and challenging jobs to motivate exemplary performers. The study also shows that the rewards offered as a result of good performance were worthwhile and meaningful. The study concluded that employees reward systems is a source of motivation to the employees.
RESEARCH PROPOSAL MBA-HUMAN RESOURCE MANAGEMENT1. Project (re.docxronak56
RESEARCH PROPOSAL: MBA-HUMAN RESOURCE MANAGEMENT
1. Project (research topic) title
The title of this proposal is: "Effectiveness of Reward System and Appraisals System in increasing the Retention and Productivity of employees in Retail Sector"
2. Project (research topic) summary
In no more than 100 words, intelligible to a reader who is not a specialist in this field, summarize the aims, significance and expected outcomes of your proposed research.
Project summary:
Organizations and the business sectors use the system of appraisal to gauge the performance of the various employees. Moreover, rewarding of well-performing employees is a motivation to the employees. This project aims a studying the effective systems of appraisal and rewarding in the retail business. Effective appraisal systems ensure that there is progress in the organization. Effective appraisal systems are appreciated by the employees and are the basis of retaining good performing employees. The proposal aims at providing an understanding effectiveness of systems of rewarding and appraisal to the performance and retention of the employees.
3. Project (research topic) details
3.1 Introductory background
The human resource department plays an important role in ensuring that all units of a business are integrated. They do this by employee management; performing appraisals and rewarding of well-performing employees. Rewards appraisal is significant in raising the employee motivation and levels of performances (Hendry, 2012).
3.2 Research questions
The research question aims to answer the effects of rewarding and appraisal system in the business. The research questions include:
· What is the system of rewarding in the business?
· How is the appraisal system of the business like?
· The effects of the appraisal and rewarding system on the employees
· How do the employees react to the system of appraisal?
Hypothesis
H0: Effective appraisal and rewarding systems in a retail organization lead to employee retention in the retail organization.
H1: Effective appraisal and rewarding systems in a retail organization lead to increased employee productivity in the retail organization.
3.3 Aims/Objectives of the project
The following are the objects of the research.
· To have an understanding of the significance of the systems of appraisal and rewarding in the retail sector.
· To have an understanding of the impact of rewarding and appraisal system on employee productivity.
· To have an understanding of the employees the systems used to appraise and reward employees for their retention.
· To understand the importance of reward and appraisal systems in the retail organization.
· To understand the extent of employee retention through effective reward and appraisal system.
· To understand the increase in productivity that is related to reward and appraisal system.
3.4 Significance/Contribution to the discipline
In the organizations, the rewarding and appraisal systems hav ...
Improving Productivity through Appropriate Performance Appraisal in Pakistan ...Muhammad Arslan
The purpose of this study is to analyze the impact of performance appraisal on productivity. Appraisal tools are
used to measure the output of workers which are compared with the given tasks with specific working
environment in designing these tools there is three step process define the job, appraise the performance and
providing the relative feedback. The manager should take keen in designing. Cross tabulation methods is used to
analyze this phenomenon. Face to face interview and questionnaire will be the research strategy and this will be
cross sectional study i.e. one time study; data collection method will be secondary data, primary data through
random sampling will be collected from the contractors of transport companies of Pakistan State Oil Limited
and general analytical method will be used for data analysis. The finding of study suggests that performance
appraisal system has significant effect on personal skill and by using the combination of two methods; rating and
narrative method leads us improvement in productivity of the organization.
Similar to Impact of Perceived Fairness on Performance Appraisal System for Academic Staff- General Sir Jhon Kotelawala Defence University (20)
Teacher Educators’ and Student Teachers’ Attitude towards Teacher Education P...IJSRP Journal
Attitudes vary at different times of one’s life and are usually determined by several factors such as work environment, job satisfaction and status of the profession. Both student-teachers’ and teacher-educators’ attitudes may affect the quality of teacher preparation program and finally quality of the teacher either positively or negatively. This paper is a focus on the attitude of teacher educators and student teachers towards teacher education programmes in universities. The study adopted a descriptive survey design. The study sample consisted of Bachelor of Education fourth year students drawn from three Public universities and three Private universities, Teacher Educators and Heads of Departments from the faculty of Education. Stratified random sampling was used to select the universities, student-teachers and Teacher Educators. Data was collected using questionnaires, interview schedules, observation checklists and documents analysis. Data was analyzed using descriptive statistics. The study found that a large percentage of the respondents portrayed a negative attitude of teacher education programmes. This may be to the fact that most student teachers and teacher educators enrolled in these programmes, do not have teaching as their professional interest thus join by circumstance. The study recommends the need to conduct screening of individuals before admission in teacher education programmes so as to ensure that only those who are interested and committed to teaching as a profession are enrolled. Keywords: Attitude, Teacher Education Programmes, Enrollment, Teacher Educators, Student Teachers, Public University, Private University
Development of a Novel Robust Differential Maximum Power Point Tracking (MPPT...IJSRP Journal
The use of photovoltaic (PV) systems is increasingly growing in importance since they involve an exploitation of solar radiation constituting an energy source which is renewable, available in most places, and pollution-free. Despite their numerous advantages, PV systems have two major drawbacks: low energy conversion efficiency and loss of energy due to variations in meteorological conditions; for this reason, Maximum Power Point Tracking (MPPT) control techniques play a key role in exploiting the maximum energy caught by PV modules. The output characteristic of a photovoltaic array is nonlinear and changes with solar irradiation and the cell’s temperature. Therefore, a Maximum Power Point Tracking (MPPT) technique is needed to draw peak power from the solar array to maximize the produced energy. In this study we have analyzed the Maximum Power Point Tracking (MPPT) method and finding out a new and easier way to track maximum power point (MPP) and also our study is focused to overcome the drawbacks of MPPT. This research paper presents a novel MPP tracking method for tracking exact Maximum Power Point (MPP) if the irradiation or load changes.
Efficacy of Anti-Melanogenic and Anti-Ageing Properties of Glutathione with A...IJSRP Journal
Widespread concerns regarding the rise in prevalence of skin cancer and the adverse effects of both acute and chronic photo-damage due to exposure to UV rays, has led to various modes of treatment. The latest development in this regard is the findings about Glutathione and Polypodium dry extract as potential treatment components for skin conditions. Glutathione plays pivotal role in protecting cells against oxidative stressinduced cellular damage and in detoxifying Xenobiotics and drug metabolism. The added photo-protective effects of oral Polypodium with its antioxidant, immunoregulatory and antiinflammatory properties aid also in prevention of chronic skin damage, photoaging, and skin cancer led by UV exposure. Its decreased levels are associated with the common features of aging as well as of a wide range of pathological conditions, including neurodegenerative disorders.
Spatial Disparities in Access and Use of Rehabilitation Services in Northern ...IJSRP Journal
This document summarizes a study that used geographic information systems (GIS) to analyze spatial disparities in access to rehabilitation services in Imathia, Greece. The study reviewed medical records of 1,005 patients who received rehabilitation services for musculoskeletal disorders at a public hospital in Imathia over two years. GIS mapping showed that most patients (60.5%) lived near the hospital, indicating greater access for nearby areas. Maps of male and female patients confirmed spatial inequalities in accessibility between neighboring locations. The results raise important questions for further investigating the causes of these disparities in access to rehabilitation services across the region.
Does Electronic Medical Records make cost benefits to non-profit seeking heal...IJSRP Journal
Sri Lanka provides a free public health care service to its permanent residents. Currently Sri Lankan health care system is in the process of using EMR systems both public and private sector healthcare institutions. There are few published data available regarding cost-benefits of EMR in profit seeking institutes in some countries and no published data on non-profit seeking institutes. Therefore, main objective of the study is to perform a cost benefit analysis (CBA) of EMRs in the public health care system in Sri Lanka and secondary objectives are to evaluate the perception of EMRs among patients, health care professionals and supporting staff. Methodology: Two Sri Lankan government hospitals’ OPDs; hospitals belong to Type A divisional category, were selected for the study. Those two hospitals were named as Hospital D and Hospital AR. Hospital D has an EMR system and hospital AR has traditional paper-based recording. A modified cost- benefit analysis was done using achievable costs and benefits. Meanwhile, three different questionnaires were distributed among health care professionals, supporting staff and patients to determine their perception on EMRs. Results: This study found that Benefits-to-Costs ratio of OPD of the hospital D for the year 2015 was 0.269 and for hospital AR was 0.0589. From CBA four basic cost reductions were found as costs for stationeries, patient queue waiting time, supporting staff number and indirect costs such as drug balancing. Health care professionals, supporting staff and patients had a positive perception on EMR systems. Conclusion: Implementing EMRs to Sri Lankan health care system leads to cost reductions. If Sri Lankan government implements an EMR system only in OPDs of government hospitals, it will lead to save millions of rupees. There are thirty-five, Type A divisional hospitals in Sri Lanka. If this EMR system is implemented only in OPDs, Sri Lankan public health care system would have saved Rs192 million ($ 1.3 million) in 2015.Finally, it can be concluded that implementing EMRs in non-profit seeking health care institutes lead to cost reductions and save money.
User Delinquency in Law College Library, Sri Lanka: perception of the StudentsIJSRP Journal
- The document summarizes a study on user delinquency and abuse of library materials at the Sri Lanka Law College library. It found that the most common forms of abuse were tearing pages, writing notes, and highlighting. The main reasons for abuse were rare materials not being allowed to photocopy and an inadequate number of copies. Students proposed increasing copies, improving photocopy services, and introducing electronic security systems like RFID to protect materials.
Environmental Impact Assessment of Kota Super Thermal Power Station IJSRP Journal
Environmental Impact Assessment (EIA) is an important management tool for ensuring optimal use of natural resources for sustainable development. A beginning in this direction was made in our country with the impact assessment of river valley projects in 1978-79 and the scope has subsequently been enhanced to cover other developmental sectors such as industries, thermal power projects, mining schemes etc. To facilitate collection of environmental data and preparation of management plans, guidelines have been evolved and circulated to the concerned Central and State Government Departments. EIA has now been made mandatory under the Environmental (Protection Act, 1986 for 29 categories of developmental activities involving investments of Rs. 50 crores and above. In present study we have studied environmental aspects of kota super thermal power on Kota city.The KSTPS in Rajasthan was commissioned in 1983 and presently operating at 1045MW capacity,The Kota Super Thermal Power Station came in five stages and a total of 7 units have been commissioned.KSTPS is situated at the left bank of “Chambal River” in Rajasthan principal industrial city Kota.The present total area covered under KSTPS is 688 ha.The power generation system comprises mainly boiler, turbine, generator and transformers with accessories all arranged to operate as complementary parts of a common monolithic set.The allowable limits for discharge of water as specified in Schedule 4 of Environmental Protection Act And Amendment 1983 isAmmonical Nitrogen 50,Arsenic-0.2,Biochemical oxygen demand-30,Cadmium -2, Chemical oxygen demand -250, Chromium hexavalent-0.1, Chromium total-2, Copper-3,Cyanide-0.1,Fluoride-2,PH-5.5-9.0Phenols-1,Dissolve Phosphate -5,Residual Chloride 1,Sulphide 2,Total Suspended Solid 100,Zinc 5.0 . Various effluent samples are analysed to assess the effluent quality from KSTPS.Any major industrial activity have tendency to degrade the environment viz. air environment, water, noise, land and biological also. It is duty of every industry it should have its own environmental unit that allow to minimum quantity of pollutants emit into environmental and keep this pollutant range with in permissible limit described according to central and state pollution control board and MOEF. So we should think in the terms of sustainable development means development without destruction.
Study of fingertip pattern in Carcinoma Cervix patientIJSRP Journal
Dermatoglyphic study to correlate a particular dermatoglyphic pattern with occurrence of cervical carcinoma in the Northern Bengal population was done for a period of one year (July2015 to June 2016). Fingertip patterns of 72 cases of cervical carcinoma were tested against 72 controls. The results showed a statistically significant decrease in the frequency of ulnar loop pattern in cervical cancer patients(52.78%) compared to control group(60.83%) in both the hands. There is decrease in the percentage of Radial loops in cervical cancer patients (3.19%) compared to control group (7.36%) in both hands and the difference is statistically significant. The percentage of whorls decreased in control group (27.50%) compared to cervical cancer patients (38.89%) and the difference is statistically significant in both hands.
This document presents a case study of a 39-year old female patient diagnosed with Wergner's Granulomatosis (WG). She presented with left ear itching and drainage. Testing showed positive ANCA and PR3 antibodies. Imaging found lesions in the lung, ear, and sinus involvement. She was diagnosed with WG based on her clinical presentation and test results. She was treated with cyclophosphamide, corticosteroids, antibiotics, and other medications. WG is a rare autoimmune disease that involves inflammation and damage of small blood vessels. It commonly involves the upper respiratory tract, lungs, and kidneys. Without treatment, it can be fatal but prognosis has improved with immunosuppressive therapies.
Grey Multi Criteria Decision Making MethodsIJSRP Journal
Multi-Criteria Decision Making is the most well-known branch of decision making. In some cases, determining precisely the exact value of attributes is difficult and their values can be considered as Uncertain data. This paper presents two different Multi Criteria Decision Making methods based on grey numbers. The two methods are used to obtain the final ranking of the alternatives and select the best one under grey numbers. Finally, an illustrative example is presented and the results are analyzed.
Impact of Social Media among Students’ Behaviors in Tertiary Institution of A...IJSRP Journal
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Impact of Perceived Fairness on Performance Appraisal System for Academic Staff- General Sir Jhon Kotelawala Defence University
1. International Journal of Scientific and Research Publications, Volume 8, Issue 5, May 2018 8
ISSN 2250-3153
http://dx.doi.org/10.29322/IJSRP.8.5.2018.p7704 www.ijsrp.org
Impact of Perceived Fairness on Performance Appraisal
System for Academic Staff- General Sir Jhon Kotelawala
Defence University
P.L.L.C.P. Alwis
General Sir John Kotelawala Defence University
DOI: 10.29322/IJSRP.8.5.2018.p7704
http://dx.doi.org/10.29322/IJSRP.8.5.2018.p7704
Abstract- This study investigates the employees’ perception of
fairness in the performance appraisal system for academic staff
of the General Sir Jhon Kotelawala Defence University.
The perception of fairness in performance appraisal
system consists of three main factors: Distributive justice,
procedural justice, performance feedback and are used as
independent variables and effectiveness of the performance
appraisal system as dependent variable. The survey method by
using random sampling technique was used to collect the data
from academic staff.
Data analysis was conducted by using bivariate correlation
and multiple regression analysis. The findings of the result
explored that distributive, procedural and performance feedback
in the appraisal system are the three significant variables that
affect the effectiveness of the performance appraisal system
Index Terms- Perceived Fairness, performance appraisal system
I. INTRODUCTION
erformance appraisal system is considered as the most
important instrument to measure the performance of an
employee. Therefore the effectiveness of a performance appraisal
system is crucial for the employee development as well as the
development of the organization. The reason is that the appraisal
system contributes for rewarding, promoting, demoting,
terminating of an employee.
The performance evaluation of academic staff at
Kotelawala Defence University is carried out by means of a
format called “Annual Increment Form which is completed by
the raters only. This evaluation is carried out for the sole purpose
of granting the annual increment. However, it does not actually
taking in to consideration of an individual staff member’s
performance progress during the period being evaluated. This
format is distributed to the raters by the University
administration in a confidential cover.
The process of performance appraisal lacks a proper
structure and consistency with respect to organizational goals.
Therefore, the higher management of the university is in search
of an effective appraisal system for the academic members of the
university. Therefore, it is important to achieve the perceived
fairness in the performance appraisal system.
This study aims to investigate the relationship and the
correlation between distributive justice, procedural justice and
performance feedback as independent variables and effectiveness
of the appraisal system as the dependent variable.
1. Distributive Justice
Distributive justice is about the perception of individual
regarding the fairness of rewards with respect to attained goals or
contributed efforts (Colquitt, 2001 Distributive justice refers to
the perceived fairness of an individual's outcomes in proportion
to the individual's inputs as compared with the outcomes and
inputs of relevant others (Bartol, Durham, & Poon,
2001;Elverfeldt AV, 2005).
2. Procedural Justice
Procedural justice is perception of individual about the
procedures used to make decision about rewards and to what
extend the process is independent and rational for all (Greenberg
& Folger, 1983; Mount, 1983, 1984; Pooyan & Eberhardt, 1989).
Procedural justice is measured by assessing the process of
procedural rules (Colquitt, 2001) and the process used in making
and implementing resource allocation decisions (Bartol et al.,
2001). Fairness issues concerning the methods, mechanisms, and
processes used to determine outcomes. (Elverfeldt AV, 2005)
3. Performance Feedback
According to Elverfeldt AV, 2005, giving feedback to the
employee generally aims at improving performance effectiveness
through stimulating behavioural change. Thus is the manner in
which employees receive feedback on their job performance a
major factor in determining the success of the performance
appraisal system (Harris, 1988). Hearing information about the
self-discrepant from ones self-image is often difficult and
painful. Thus, because feedback may strike at the core of a
person’s personal belief system it is crucial to set conditions of
feedback so that the ratee is able to tolerate, hear, and own
discrepant information (Dalton, 1996). Only if conditions
facilitate the acceptance of feedback information then the
likelihood of change increases. Dalton (1996) further specifies
these conditions: The feedback event should be a confidential
interaction between a qualified and credible feedback giver and
ratee to avoid denial, venting of emotions, and
P
2. International Journal of Scientific and Research Publications, Volume 8, Issue 5, May 2018 9
ISSN 2250-3153
http://dx.doi.org/10.29322/IJSRP.8.5.2018.p7704 www.ijsrp.org
behavioural and mental disengagement. In such an atmosphere
discrepancies in evaluations can be discussed and the session can
be used as a catalyst to reduce the discrepancies (Jacobs et al.,
1980; Elverfeldt AV, 2005)
II. METHODOLOGY AND EXPERIMENTAL DESIGN
The author considers the whole population of civil
Academic Members of KDU in the year 2015. The total number
of academic members is 166, ranging from Lecturer
(Probationary), to Senior Lecturer Grade I from the population of
the study. Assistant and Senior Assistant Librarians too are taken
as academics as defined by the University Grants Commission.
The sample in this research was civilian academic staff
members of General Sir John Kotelawala Defence University
with the number of 118 academia. Sample size was determined
using Krejcie and Morgan (1970) method. Stratified random
sampling method was used and a computer based random
number generator was used to select the academic members at
each level.
The study involved quantitative methods to collect data by
means of a structured pre tested questionnaire. Before the actual
study was conducted, a pilot study was carried out to test the
validity and reliability of instrument used. For the actual study,
the quantitative data was collected by distributing the
questionnaire to the academic staff of the university.
The items on the questionnaire are responded to using a 5-
point Likert scale ranging from absolute disagreement, through
disagree, neutral, agree, and ending in absolute agreement.
Numerical ratings for the responses can be obtained by using
values ranging from one point for “absolute disagreement “to
five points for “absolute agreement”. The response scale is
clearly ordinal. However the responses were assigned the values
1, 2, 3, 4, 5 and averages were computed during the analysis.
The questionnaire consists of 58 questions. It measures the
level of effectiveness of the appraisal system by the means of
independent variables, user’s characteristics, perceived fairness
and system characteristics.
Methods of Data Analysis
Data was analyzed using SPSS (Statistical Packages for the
Social Scientist) statistical package which was set at the 0.05
significance level. The level of effectiveness of the existing
appraisal system will be determined using the results of
questionnaires in terms of user’s characteristics, perceived
fairness and system characteristics.
All independent variables were given marks between one to
five (1-5) for the analysis purpose. Allocation of marks for the
respondent’s answers is as follows.
Table 01
Allocation of Marks
All data was analyzed by using mean value of the factors.
Those mean values are interpreted as follows.
Table 02
Interpretation of Mean Values
Mean Value Level of Effectiveness
Mean value between 4-5 Highly effective
Mean value between 3- 3.999
Mean value between 2 -2.999
Effective
Ineffective
Mean value below 2 Highly Ineffective
The level of effectiveness for each factor of the
questionnaire was analyzed using mean and standard deviation.
The relationship of effectiveness of appraisal system and the
variables; distributive justice, procedural justice and performance
feedback were analyzed using Pearson’s correlation and
coefficient. The statistically significant factors that affect
effectiveness of PAS were determined by Analysis of variance
test.
Figure 01 illustrates the conceptual framework of this research.
Figure 01
Conceptual Framework
Independent Variables Dependent Variable
III. RESULTS
The Level of Effectiveness of the Existing Performance
Appraisal System, in Terms of Distributive Justice,
Procedural Justice and Performance Feedback.
Answer Marks
Absolute Disagreement 01
Disagreement 02
Neutral 03
Agree 04
Absolute Agreement 05
Distributive
Justice
Procedural
Justice
Performance
Feedback
Effectiveness of
performance
appraisal system
3. International Journal of Scientific and Research Publications, Volume 8, Issue 5, May 2018 10
ISSN 2250-3153
http://dx.doi.org/10.29322/IJSRP.8.5.2018.p7704 www.ijsrp.org
Table 03 Descriptive Statistics of Perceived Level of
effectiveness of PAS in Terms of Distributive Justice, Procedural
Justice and Performance Feedback. (N =62)
Correlation Analysis between Independent and Dependent
Variables.
Table 04
Correlation Analysis between Overall Effectiveness of
performance appraisal system and Independent Variables
(Distributive Justice, Procedural Justice and Performance
Feedback)
**. Correlation is significant at the 0.01 level (2-tailed)
Multiple Regression Analysis between Independent Variables
Related to Effectiveness of performance appraisal system.
Table 05
Regression Analysis between Independent Variables and
Effectiveness of performance appraisal system (Model
Summary)
Table 06
Regression Analysis between Independent Variables and
Effectiveness of performance appraisal system (Coefficients).
IV. DISCUSSION
The total mean for Distributive Justice was 1.9960, which
indicates that the respondents perceived that the existing
Performance Appraisal System is ineffective in terms of
Distributive Justice. Procedural Justice and Performance
Feedback showed means of 2.1355 and 2.0258 respectively.
Again it can be concluded that the existing Performance
Appraisal System is Ineffective.
There is a significant positive linear relationship of
effectiveness of Performance Appraisal System and all three
independent variables. The relationships are 80.2% for
Distributive Justice, 84.9% for Procedural Justice and 83% for
Performance Feedback. All three variables have very high
positive relationship almost equally.
Model summary shows that the value of R-square for the
model is 0.782. This means that 78.2 percent of the variation in
the effectiveness of Performance Appraisal System (dependent
variable) can be explained from the three independent variables.
The adjusted R-square for the model is 0.765, which indicates
only a slight overestimate with the model. The standard error of
the estimate is only 0.40259.
Regression coefficients represent the mean change in the
response variable for one unit of change in the predictor variable
while holding other predictors in the model constant. A low p-
value (< 0.05) of variables indicates that the changes in the
independent variables were related to changes in response
variable, effectiveness of PAS. Conversely, a larger
(insignificant) p value suggests that changes in the predictor are
not associated with changes in the response. Therefore, the
analysis demonstrated that the most significant positively related
factor was the procedural justice. It has scored a p value of 0.010
and Beta value of 0.455 It denotes that change of procedural
justice by one item may affect the effectiveness by 45.5%.
The fairness of Performance Appraisal System needs to be
increased in terms of distributive justice, procedural justice and
performance feedback. The fairness of granting rewards to
academia should be increased by making the appraisal unbiased,
Variable Mean
Std.
Deviation
Level of
Effectivenes
s
Distributive
Justice
1.9960 1.03275 Highly
Ineffective
Procedural
Justice
2.1355 1.06926 Ineffective
Performance
Feedback
2.0258 1.10882 Ineffective
Effectiveness of PAS
Variable
Pearson
Correlation
Sig.
(2tailed)
Effectiveness
of PAS
1
Distributive
Justice
.802**
.000
Procedural
Justice
.849**
.000
Performance
Feedback
.830**
.000
Model Summary
Mode
l
R
R
Square
Adjuste
d R
Square
Std. Error of
the Estimate
1 .884 .782 .765 .40259
Model
Unstandardiz
ed
Coefficients
Standardiz
ed
Coefficients t Sig.
B
Std.
Error
Beta
(Constant)
.218 .138 .762
.45
2
Distributive
justice
.188 .128 .215 .183
.85
6
Procedural
justice
.404 .126 .455
2.72
9
.01
0
Performanc
e feedback
.236 .143 .269 .350
.72
8
a.
Dependent Variable: Effectiveness PAS
4. International Journal of Scientific and Research Publications, Volume 8, Issue 5, May 2018 11
ISSN 2250-3153
http://dx.doi.org/10.29322/IJSRP.8.5.2018.p7704 www.ijsrp.org
increased communication between supervisor and subordinate,
output related rewards and design the Performance Appraisal
System leading to better performance and better work quality.
The Performance Appraisal System should highly focus on
procedural justice. Objective measures should be designed to
appraisal. The standards should be clearly defined to evaluate the
performance. Clear instructions should be given to a both raters
and ratees. The standards should be simple and clear. The ratings
should be available for review as well. They should be able to
discuss problems in relation to their performance evaluation with
the supervisor. A follow up system should be incorporated to
Performance Appraisal System to monitor whether the raters
follow the said standards properly in case of a particular
individual as well as in the equal manner for others.
The component of giving feedback should be focused on
the new Performance Appraisal System. Feedback of an
individual may lead to denial, venting of emotions, and
behavioral and mental disengagement. Designing of Performance
Appraisal System should address above issues. It should be
strictly confidential, constructive and should lead the academia
towards achieving expected goals. In this regard the Performance
Appraisal System can identify future training needs of the ratees.
Student feedback and peer review should also be included in the
appraisal form.
V. CONCLUSION
In conclusion, author has identified the fairness of a
performance appraisal system has crucial effect on the success of
the organization as the perceived fairness has a relationship with
the agreement of the system and as the end result the
performance of the academic staff.
The academia are very vigilant about the fairness based on
the appraisal system, how the head of departments treat them,
and the end result. Hence, the fairness of an appraisal system
affect all dimensions of academia in the university. Therefore the
higher authority should take necessary steps to upsurge the
fairness level of the Performance Appraisal System for academic
staff at General Sir Jhon Kotelawala Defence University.
ACKNOWLEDGMENT
This research was supported by the General Sir John
Kotelawala Defence University. I thank Prof GTF Silva who
provided insight and expertise that greatly assisted the research.
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AUTHORS
First Author – P.L.L.C.P. Alwis, General Sir John Kotelawala
Defence University, charithangi@yahoo.com