Tribhuvan University, Nepal
Masters in Arts
Population Studies
Research method in Population analysis
Validity and Threats to validity
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This document discusses the concept of reliability in testing. It provides several definitions of reliability from dictionaries and researchers. Reliability refers to the consistency and repeatability of test results. The document outlines different types of reliability, including test-retest reliability, parallel-form reliability, and internal consistency reliability. It also discusses factors that can affect reliability, such as test length, heterogeneity of scores, difficulty level, test administration, scoring, and the passage of time between test administrations. Controlling for these factors can improve a test's reliability.
Standardized tests are designed and administered consistently to allow for comparison of student performance. Tests are given to a sample group to determine average scores and the spread of scores. This establishes norms that individual students can be compared to. There are two main types of standardized tests - norm-referenced tests which compare students to peers, and criterion-referenced tests which assess knowledge of a defined subject area. Tests go through a process of development that includes trying out drafts, analyzing results, revising weak questions, and further testing to establish reliability and validity.
Reliability refers to the consistency of a measure. There are several types of reliability: test-retest, equivalency, inter-rater, and internal consistency. Test-retest reliability assesses consistency over time, equivalency assesses consistency between alternate forms, inter-rater assesses consistency between raters, and internal consistency assesses consistency between items. Factors like memory, practice effects, and maturation can impact reliability over time. Reliability is important for a measure to be valid and useful. Ways to improve reliability include making tests longer, carefully constructing items, and standardizing administration procedures.
This document defines key terms related to reliability and discusses various methods for measuring reliability. It defines reliability as consistency in measurement and discusses sources of error such as test construction, administration, and scoring. It then covers classical test theory, domain sampling theory, item response theory, generalizability theory, and various methods to measure reliability including test-retest, parallel/alternate forms, split-half, inter-item consistency, inter-scorer, and standard error of measurement. It concludes with ways to improve reliability such as using quality test items, adequately sampling content, developing a scoring plan, and ensuring validity.
The document discusses different types of aptitude tests. It defines aptitude as an individual's ability or talent to perform certain tasks, as measured through aptitude tests. There are three main categories of aptitude tests: general aptitude tests, special aptitude tests, and manual dexterity tests. General aptitude tests measure abilities like reasoning, numeracy, language skills, and are further divided into general aptitude test batteries and differential aptitude tests. Special aptitude tests examine abilities related to specific domains like mechanics, clerical work, aesthetics, and music. Manual dexterity tests evaluate hand-eye coordination and finger movement.
Reliability refers to the consistency or repeatability of measurement results. There are four types of reliability: inter-rater, parallel forms, test-retest, and internal consistency. Reliability can be estimated using external consistency procedures, which compare results from independent data collection processes, or internal consistency procedures, which assess consistency across items in the same test.
Aptitude (Test) and their Nature and CharacteristicsSubhankar Rana
Aptitude is a future potentiality of an individual therefore we predict a person's future success in a particular field.
#Aptitude #Measurement & Evaluation #Achievement #Future potentiality #Ability
Topic: What is Reliability and its Types?
Student Name: Kanwal Naz
Class: B.Ed 1.5
Project Name: “Young Teachers' Professional Development (TPD)"
"Project Founder: Prof. Dr. Amjad Ali Arain
Faculty of Education, University of Sindh, Pakistan
This document discusses the concept of reliability in testing. It provides several definitions of reliability from dictionaries and researchers. Reliability refers to the consistency and repeatability of test results. The document outlines different types of reliability, including test-retest reliability, parallel-form reliability, and internal consistency reliability. It also discusses factors that can affect reliability, such as test length, heterogeneity of scores, difficulty level, test administration, scoring, and the passage of time between test administrations. Controlling for these factors can improve a test's reliability.
Standardized tests are designed and administered consistently to allow for comparison of student performance. Tests are given to a sample group to determine average scores and the spread of scores. This establishes norms that individual students can be compared to. There are two main types of standardized tests - norm-referenced tests which compare students to peers, and criterion-referenced tests which assess knowledge of a defined subject area. Tests go through a process of development that includes trying out drafts, analyzing results, revising weak questions, and further testing to establish reliability and validity.
Reliability refers to the consistency of a measure. There are several types of reliability: test-retest, equivalency, inter-rater, and internal consistency. Test-retest reliability assesses consistency over time, equivalency assesses consistency between alternate forms, inter-rater assesses consistency between raters, and internal consistency assesses consistency between items. Factors like memory, practice effects, and maturation can impact reliability over time. Reliability is important for a measure to be valid and useful. Ways to improve reliability include making tests longer, carefully constructing items, and standardizing administration procedures.
This document defines key terms related to reliability and discusses various methods for measuring reliability. It defines reliability as consistency in measurement and discusses sources of error such as test construction, administration, and scoring. It then covers classical test theory, domain sampling theory, item response theory, generalizability theory, and various methods to measure reliability including test-retest, parallel/alternate forms, split-half, inter-item consistency, inter-scorer, and standard error of measurement. It concludes with ways to improve reliability such as using quality test items, adequately sampling content, developing a scoring plan, and ensuring validity.
The document discusses different types of aptitude tests. It defines aptitude as an individual's ability or talent to perform certain tasks, as measured through aptitude tests. There are three main categories of aptitude tests: general aptitude tests, special aptitude tests, and manual dexterity tests. General aptitude tests measure abilities like reasoning, numeracy, language skills, and are further divided into general aptitude test batteries and differential aptitude tests. Special aptitude tests examine abilities related to specific domains like mechanics, clerical work, aesthetics, and music. Manual dexterity tests evaluate hand-eye coordination and finger movement.
Reliability refers to the consistency or repeatability of measurement results. There are four types of reliability: inter-rater, parallel forms, test-retest, and internal consistency. Reliability can be estimated using external consistency procedures, which compare results from independent data collection processes, or internal consistency procedures, which assess consistency across items in the same test.
Aptitude (Test) and their Nature and CharacteristicsSubhankar Rana
Aptitude is a future potentiality of an individual therefore we predict a person's future success in a particular field.
#Aptitude #Measurement & Evaluation #Achievement #Future potentiality #Ability
Topic: What is Reliability and its Types?
Student Name: Kanwal Naz
Class: B.Ed 1.5
Project Name: “Young Teachers' Professional Development (TPD)"
"Project Founder: Prof. Dr. Amjad Ali Arain
Faculty of Education, University of Sindh, Pakistan
This document discusses the key characteristics of a good measuring instrument or test, including validity, reliability, objectivity, norms, and usability. It defines validity as the accuracy with which a test measures what it claims to measure, and describes different types of validity including content validity, criterion-related validity, and construct validity. Reliability is defined as the consistency of measurement and different methods for estimating reliability are outlined. Objectivity refers to eliminating personal bias from scoring. Norms provide average scores for comparison. Usability factors like ease of administration, timing, cost, and scoring are also addressed.
The document discusses intelligence testing and provides definitions of intelligence. It describes different types of intelligence tests including individual tests, group tests, verbal tests, and non-verbal tests. Specific intelligence tests are explained like the Wechsler tests, Stanford-Binet test, Raven's Progressive Matrices, and Vineland Social Maturity Scale. The uses and conclusions of intelligence testing are also summarized.
Variables: Types and their Operational Definitions
Unit III: Problem identification formulation of research objectives and hypothesis (as part of M.Optom Curriculum of Pokhara University, Nepal)
1. types of psychological tests by S.Lakshmanan PsychologistLAKSHMANAN S
My sincere thanks to: - Professor Dr. V.Suresh
Annamalai University
Dear Viewers, Please, See this updated version of the types of psychological tests in this www.slideshare.net
This document discusses the concept of validity in psychological testing. It defines validity as the degree to which a test measures what it claims to measure. There are three main types of validity: content validity, which concerns how well a test represents the content area it aims to measure; criterion-related validity, which compares test scores to external criteria; and construct validity, which evaluates how well a test measures hypothetical constructs. Validity is influenced by factors like test length and the range of abilities in the sample population. A test must demonstrate validity to ensure the inferences made from its results are appropriate and meaningful.
This document discusses validity and reliability in quantitative research. It defines validity as the ability of an instrument to measure what it is designed to measure, and reliability as the consistency of measurements. There are several types of validity, including face validity, content validity, criterion validity, and construct validity. Reliability can be measured through test-retest reliability, parallel-forms reliability, and internal consistency reliability. Both validity and reliability are important for research quality and ensuring an instrument accurately measures the intended construct. A test cannot be considered valid without also being reliable.
Psychological test norms are based on large standardization samples that are representative of the population for which the test is intended. Tests are standardized by administering them to samples stratified on key demographics like age, gender, education level, and geographical region to create a normal distribution of scores. This allows future test takers' raw scores to be converted to percentiles for accurate comparison against the norm group. Regularly updating test norms with new standardization samples is important for interpreting scores.
This document discusses two types of pre-experimental design: one-shot case design and one group pre-test post-test design. The one-shot case design involves exposing a single experimental group to a treatment and observing the results with no control group. The one group pre-test post-test design selects an experimental group, takes a pre-test measurement, administers a treatment, then takes a post-test measurement to assess the treatment's effect with no control group. While simple and convenient, pre-experimental designs have high threats to internal validity and are weak for establishing causation between variables.
The document discusses various perspectives on intelligence and the history and types of intelligence tests. It defines intelligence as the ability to think, solve problems, and understand social norms. It outlines theories of intelligence from Wechsler, Neisser, Gardner that proposed multiple types of intelligence. The history of intelligence testing is reviewed from Binet's early IQ tests to current tests like the WAIS and WISC. Intelligence tests are described as measuring problem solving, comprehension, and reasoning abilities.
This document provides information about intelligence tests. It defines intelligence and discusses key figures in the development of intelligence testing like Alfred Binet and Theodore Simon who created the first intelligence test. It describes different types of intelligence tests including individual verbal tests like the Stanford-Binet test, individual non-verbal tests involving tasks like block building, and group tests with verbal and non-verbal components. The document also discusses intelligence quotients (IQ) and classifications of IQ scores.
Interest by S.Lakshmanan, PsychologistLAKSHMANAN S
This document discusses interest and how it relates to personality and career guidance. It defines interest as a feeling of liking associated with an activity. Interests are shaped by both heredity and environment and vary between individuals and over time. There are different types of interests including intrinsic, extrinsic, expressed, and manifested. Interests can be assessed through tests, inventories, and questionnaires. Commonly used interest inventories include Strong's Vocational Interest Blank, Kuder's Preference Record, and Thurstone's Interest Blank. The results of interest assessments can provide useful information to help with educational and career guidance.
Reliability refers to the consistency of test scores. There are three main types of reliability: stability, equivalence, and homogeneity. Stability measures consistency over time, equivalence uses alternative versions of a test, and homogeneity examines internal consistency. Factors like data collection methods, time intervals, and test administration can influence reliability. To improve reliability, tests should have clear, unambiguous questions and objective scoring. Rater reliability specifically measures consistency between raters or judges.
This document discusses the different types of validity in psychological testing: face validity, content validity, criterion validity (including predictive and concurrent validity), and discriminant validity. It provides examples for each type of validity. Criterion validity refers to how a test correlates with other measures of the same construct. Discriminant validity shows a test does not correlate with measures of different constructs. Validity is determined through empirical evidence over many studies, and is not an all-or-none concept. Factors like history, maturation, testing, and selection can threaten a test's validity if not controlled.
This document discusses methods for estimating the reliability of tests, including test-retest reliability, parallel forms reliability, and internal consistency reliability. It describes the split-half approach for estimating internal consistency reliability using a single test administration. This involves splitting the test into two halves and correlating scores. It discusses three methods for splitting tests - odd-even, ordered, and matched random subsets. The document also generalizes these concepts to splitting tests into multiple components. Estimates of internal consistency reliability provide a lower bound for a test's actual reliability if components are not equivalent.
Reliability refers to the consistency of test scores. A reliable test will produce similar results over multiple test administrations. There are several methods for determining reliability, including internal consistency, test-retest reliability, inter-rater reliability, and split-half reliability. Validity refers to how well a test measures what it intends to measure. Validity can be established through face validity, construct validity, content validity, and criterion validity. Both reliability and validity are important for a high quality test, as a test can be reliable without being valid.
Internal and external validity (experimental validity)Jijo Varghese
This document discusses experimental validity, including internal and external validity. It defines internal validity as being about whether the independent variable caused changes in the dependent variable. Threats to internal validity include history, maturation, testing, instrumentation, regression, selection bias, mortality, and additive/interactive effects. External validity is about generalizing results beyond the experimental setting, and threats include interaction of selection/treatment, testing/treatment, setting/treatment, history/treatment, and the Hawthorne effect. Maintaining validity requires controlling for these threats in research design.
This document discusses various methods of assessing personality, including subjective, objective, and projective methods.
The subjective method involves self-reports like autobiographies, questionnaires, and inventories. The objective method uses observation, checklists, ratings scales, and performance/situational tests. Projective techniques include the Rorschach inkblot test, where subjects report what they perceive in inkblots, and the Thematic Apperception Test (TAT), where subjects generate stories based on ambiguous pictures. Specific tests discussed include Bell's Adjustment Inventory, case study method, sentence completion tests, and situational tests. The document concludes with precautions that should be taken when using psychological tests.
This document discusses the concept of validity in psychological testing and research. It provides definitions of validity from authoritative sources like the American Psychological Association. It distinguishes between different types of validity like construct validity, content validity, criterion validity, predictive validity, concurrent validity, and experimental validity, which includes statistical conclusion validity, internal validity, external validity, and ecological validity. The relationships between these types of validity are explored in depth through multiple examples and implications. The document emphasizes that validity concerns the appropriate interpretation and use of test scores rather than a test itself. It is intended as a guide on validity for Dr. GHIAS UL HAQ from SARHAD UNIVERSITY OF INFORMATION TECHNOLOGY, PESHAWAR.
Standardization refers to methods used in psychological research to ensure consistency and allow for comparison between groups. It involves using identical procedures, instructions, questions, timing, and conditions for all participants. This helps reduce external influences and increase reliability, validity, and the ability to establish norms based on a representative standardization sample. Ensuring standardization is crucial for obtaining unbiased and meaningful results.
This document discusses key criteria for evaluating social research: validity, reliability, causality, and replication. It defines each concept and provides examples. Validity ensures research measures what it intends to measure through constructs like internal, external, and ecological validity. Reliability ensures consistency in measures over time and between observers. Causality looks for precedence between variables and correlation not due to other factors. Replication requires explicitly detailing procedures to allow others to reproduce results and ensure objectivity. The document provides an overview of important standards for high-quality social scientific research.
This document provides an overview of interpreting quantitative research results. It discusses that statistical results must be interpreted to be useful. The key tasks of interpretation include considering the credibility, precision, magnitude, meaning, generalizability, and implications of results. Credibility refers to trustworthiness, and can be impacted by proxies, validity, bias, and corroboration. Precision concerns how close estimates are, while magnitude examines effect sizes. Inferences must make meaning of credible, precise, and important results, while considering causality. Researchers should acknowledge limitations and their impact on interpreting results.
This document discusses the key characteristics of a good measuring instrument or test, including validity, reliability, objectivity, norms, and usability. It defines validity as the accuracy with which a test measures what it claims to measure, and describes different types of validity including content validity, criterion-related validity, and construct validity. Reliability is defined as the consistency of measurement and different methods for estimating reliability are outlined. Objectivity refers to eliminating personal bias from scoring. Norms provide average scores for comparison. Usability factors like ease of administration, timing, cost, and scoring are also addressed.
The document discusses intelligence testing and provides definitions of intelligence. It describes different types of intelligence tests including individual tests, group tests, verbal tests, and non-verbal tests. Specific intelligence tests are explained like the Wechsler tests, Stanford-Binet test, Raven's Progressive Matrices, and Vineland Social Maturity Scale. The uses and conclusions of intelligence testing are also summarized.
Variables: Types and their Operational Definitions
Unit III: Problem identification formulation of research objectives and hypothesis (as part of M.Optom Curriculum of Pokhara University, Nepal)
1. types of psychological tests by S.Lakshmanan PsychologistLAKSHMANAN S
My sincere thanks to: - Professor Dr. V.Suresh
Annamalai University
Dear Viewers, Please, See this updated version of the types of psychological tests in this www.slideshare.net
This document discusses the concept of validity in psychological testing. It defines validity as the degree to which a test measures what it claims to measure. There are three main types of validity: content validity, which concerns how well a test represents the content area it aims to measure; criterion-related validity, which compares test scores to external criteria; and construct validity, which evaluates how well a test measures hypothetical constructs. Validity is influenced by factors like test length and the range of abilities in the sample population. A test must demonstrate validity to ensure the inferences made from its results are appropriate and meaningful.
This document discusses validity and reliability in quantitative research. It defines validity as the ability of an instrument to measure what it is designed to measure, and reliability as the consistency of measurements. There are several types of validity, including face validity, content validity, criterion validity, and construct validity. Reliability can be measured through test-retest reliability, parallel-forms reliability, and internal consistency reliability. Both validity and reliability are important for research quality and ensuring an instrument accurately measures the intended construct. A test cannot be considered valid without also being reliable.
Psychological test norms are based on large standardization samples that are representative of the population for which the test is intended. Tests are standardized by administering them to samples stratified on key demographics like age, gender, education level, and geographical region to create a normal distribution of scores. This allows future test takers' raw scores to be converted to percentiles for accurate comparison against the norm group. Regularly updating test norms with new standardization samples is important for interpreting scores.
This document discusses two types of pre-experimental design: one-shot case design and one group pre-test post-test design. The one-shot case design involves exposing a single experimental group to a treatment and observing the results with no control group. The one group pre-test post-test design selects an experimental group, takes a pre-test measurement, administers a treatment, then takes a post-test measurement to assess the treatment's effect with no control group. While simple and convenient, pre-experimental designs have high threats to internal validity and are weak for establishing causation between variables.
The document discusses various perspectives on intelligence and the history and types of intelligence tests. It defines intelligence as the ability to think, solve problems, and understand social norms. It outlines theories of intelligence from Wechsler, Neisser, Gardner that proposed multiple types of intelligence. The history of intelligence testing is reviewed from Binet's early IQ tests to current tests like the WAIS and WISC. Intelligence tests are described as measuring problem solving, comprehension, and reasoning abilities.
This document provides information about intelligence tests. It defines intelligence and discusses key figures in the development of intelligence testing like Alfred Binet and Theodore Simon who created the first intelligence test. It describes different types of intelligence tests including individual verbal tests like the Stanford-Binet test, individual non-verbal tests involving tasks like block building, and group tests with verbal and non-verbal components. The document also discusses intelligence quotients (IQ) and classifications of IQ scores.
Interest by S.Lakshmanan, PsychologistLAKSHMANAN S
This document discusses interest and how it relates to personality and career guidance. It defines interest as a feeling of liking associated with an activity. Interests are shaped by both heredity and environment and vary between individuals and over time. There are different types of interests including intrinsic, extrinsic, expressed, and manifested. Interests can be assessed through tests, inventories, and questionnaires. Commonly used interest inventories include Strong's Vocational Interest Blank, Kuder's Preference Record, and Thurstone's Interest Blank. The results of interest assessments can provide useful information to help with educational and career guidance.
Reliability refers to the consistency of test scores. There are three main types of reliability: stability, equivalence, and homogeneity. Stability measures consistency over time, equivalence uses alternative versions of a test, and homogeneity examines internal consistency. Factors like data collection methods, time intervals, and test administration can influence reliability. To improve reliability, tests should have clear, unambiguous questions and objective scoring. Rater reliability specifically measures consistency between raters or judges.
This document discusses the different types of validity in psychological testing: face validity, content validity, criterion validity (including predictive and concurrent validity), and discriminant validity. It provides examples for each type of validity. Criterion validity refers to how a test correlates with other measures of the same construct. Discriminant validity shows a test does not correlate with measures of different constructs. Validity is determined through empirical evidence over many studies, and is not an all-or-none concept. Factors like history, maturation, testing, and selection can threaten a test's validity if not controlled.
This document discusses methods for estimating the reliability of tests, including test-retest reliability, parallel forms reliability, and internal consistency reliability. It describes the split-half approach for estimating internal consistency reliability using a single test administration. This involves splitting the test into two halves and correlating scores. It discusses three methods for splitting tests - odd-even, ordered, and matched random subsets. The document also generalizes these concepts to splitting tests into multiple components. Estimates of internal consistency reliability provide a lower bound for a test's actual reliability if components are not equivalent.
Reliability refers to the consistency of test scores. A reliable test will produce similar results over multiple test administrations. There are several methods for determining reliability, including internal consistency, test-retest reliability, inter-rater reliability, and split-half reliability. Validity refers to how well a test measures what it intends to measure. Validity can be established through face validity, construct validity, content validity, and criterion validity. Both reliability and validity are important for a high quality test, as a test can be reliable without being valid.
Internal and external validity (experimental validity)Jijo Varghese
This document discusses experimental validity, including internal and external validity. It defines internal validity as being about whether the independent variable caused changes in the dependent variable. Threats to internal validity include history, maturation, testing, instrumentation, regression, selection bias, mortality, and additive/interactive effects. External validity is about generalizing results beyond the experimental setting, and threats include interaction of selection/treatment, testing/treatment, setting/treatment, history/treatment, and the Hawthorne effect. Maintaining validity requires controlling for these threats in research design.
This document discusses various methods of assessing personality, including subjective, objective, and projective methods.
The subjective method involves self-reports like autobiographies, questionnaires, and inventories. The objective method uses observation, checklists, ratings scales, and performance/situational tests. Projective techniques include the Rorschach inkblot test, where subjects report what they perceive in inkblots, and the Thematic Apperception Test (TAT), where subjects generate stories based on ambiguous pictures. Specific tests discussed include Bell's Adjustment Inventory, case study method, sentence completion tests, and situational tests. The document concludes with precautions that should be taken when using psychological tests.
This document discusses the concept of validity in psychological testing and research. It provides definitions of validity from authoritative sources like the American Psychological Association. It distinguishes between different types of validity like construct validity, content validity, criterion validity, predictive validity, concurrent validity, and experimental validity, which includes statistical conclusion validity, internal validity, external validity, and ecological validity. The relationships between these types of validity are explored in depth through multiple examples and implications. The document emphasizes that validity concerns the appropriate interpretation and use of test scores rather than a test itself. It is intended as a guide on validity for Dr. GHIAS UL HAQ from SARHAD UNIVERSITY OF INFORMATION TECHNOLOGY, PESHAWAR.
Standardization refers to methods used in psychological research to ensure consistency and allow for comparison between groups. It involves using identical procedures, instructions, questions, timing, and conditions for all participants. This helps reduce external influences and increase reliability, validity, and the ability to establish norms based on a representative standardization sample. Ensuring standardization is crucial for obtaining unbiased and meaningful results.
This document discusses key criteria for evaluating social research: validity, reliability, causality, and replication. It defines each concept and provides examples. Validity ensures research measures what it intends to measure through constructs like internal, external, and ecological validity. Reliability ensures consistency in measures over time and between observers. Causality looks for precedence between variables and correlation not due to other factors. Replication requires explicitly detailing procedures to allow others to reproduce results and ensure objectivity. The document provides an overview of important standards for high-quality social scientific research.
This document provides an overview of interpreting quantitative research results. It discusses that statistical results must be interpreted to be useful. The key tasks of interpretation include considering the credibility, precision, magnitude, meaning, generalizability, and implications of results. Credibility refers to trustworthiness, and can be impacted by proxies, validity, bias, and corroboration. Precision concerns how close estimates are, while magnitude examines effect sizes. Inferences must make meaning of credible, precise, and important results, while considering causality. Researchers should acknowledge limitations and their impact on interpreting results.
This document discusses validity and reliability in research. It defines validity as the extent to which a test measures what it claims to measure. Reliability is defined as the extent to which a test shows consistent results on repeated trials. The document then discusses various types of validity including content, face, criterion-related, construct, and ecological validity. It also discusses types of reliability including equivalency, stability, internal consistency, inter-rater, and intra-rater reliability. Factors affecting validity and reliability are presented along with how validity and reliability are related concepts in research.
This document discusses different types of data validity including face validity, content validity, criterion validity (predictive validity, concurrent validity, discriminant validity), external validity, internal validity, ecological validity, and population validity. It provides examples and definitions for each type of validity. Additionally, it outlines factors that can affect data validity such as history, maturation, testing, instrumentation, and selection bias. Validity is determined through empirical evidence over multiple studies and is not an all-or-none concept but rather exists on a continuum.
Quantitative, qualitive and mixed research designsAras Bozkurt
This document provides an overview of quantitative method design, specifically experimental design. It discusses key concepts in experimental design including random assignment, control over extraneous variables, manipulation of treatment conditions, outcome measures, and threats to validity. It also describes different types of experimental designs including between-group designs like true experiments, quasi-experiments, and factorial designs as well as within-group designs like time series experiments, repeated measures experiments, and single subject experiments. The document provides examples and explanations of how to implement these different experimental designs.
Internal and External threat to ValidityZehra Khushal
This document discusses research design methods in survey and experimental research. It describes key aspects of the survey method, including that it is a descriptive design that collects self-reported data through questions administered via interviews or questionnaires. Steps in survey design are outlined, including defining objectives, sampling, distribution of questionnaires, and follow-ups. Experimental design is described as the only method that can establish cause-and-effect through manipulation of independent variables and measurement of dependent variables. Types of experimental designs and threats to internal and external validity are summarized.
This document discusses validity in epidemiological studies. It defines validity as the degree to which a study accurately measures what it aims to measure. Internal validity refers to minimizing errors in data collection, while external validity is the ability to generalize results to other settings and populations. Bias, confounding, and chance can threaten validity. Bias can occur in selection of participants or measurement. Confounding involves extraneous factors associated with both exposure and outcome. Larger sample sizes and longer studies reduce the impact of chance on validity. Assessing validity involves evaluating the study design and ensuring it limits threats to validity.
This document discusses reliability and validity in testing. It defines reliability as the consistency of test measures and discusses various methods to assess reliability including test-retest, equivalent forms, internal consistency using split-half and alpha coefficient methods. The document also defines validity as the appropriateness of test inferences and discusses three types of validity evidence: content, criterion, and construct validity. It further explains threats to internal validity such as subject characteristics, location effects, and data collector bias that can influence test outcomes.
The document provides an overview of quantitative research methodology. It discusses key concepts including population, sampling, samples, and qualitative scales. Specifically, it defines population as any complete group with at least one characteristic in common. It explains that sampling is used to select a subset of a population for a study. The document also outlines different types of measurement scales in quantitative research including nominal, ordinal, interval, and ratio scales.
This document summarizes the key aspects of evaluating clinical trials. In 3 sentences:
Clinical trials aim to determine if new treatments are safe and effective by testing them on people after promising laboratory and animal studies. Different types of clinical trials exist, from uncontrolled to randomized controlled trials, with RCTs being the gold standard as they randomly assign participants to interventions to reduce bias. Properly evaluating trials involves assessing their design, limitations, and results to determine the risk of bias and whether the trial's conclusions are valid and applicable to a specific patient.
This document provides an overview of research design. It defines research design and discusses its purpose and functions, which include outlining procedures for a study and ensuring valid and objective answers. It also categorizes research design based on the number of contacts with participants (cross-sectional, before-after, longitudinal), reference period (retrospective, prospective, retrospective-prospective), and nature of the investigation (experimental, non-experimental, semi-experimental). Unique designs like action research are also mentioned. The document provides examples to illustrate different types of research designs.
The document discusses experimental research methods. It defines experimental research as applying treatments to groups and measuring their effects. It describes key aspects of experimental design including independent and dependent variables, as well as threats to internal and external validity like history, maturation, and selection bias. Finally, it outlines different experimental designs like single group, parallel group, and rotation group designs and the steps involved in conducting experimental research.
The document provides an overview of research design, defining it as a plan for how a research study will be completed. It discusses the purpose of research design, which is to help researchers make valid, objective, and economical decisions about how to complete the entire research process. The document then covers various classifications of research designs, including those based on the number of contacts with the study population, the reference period of the study, and the nature of the investigation in terms of whether variables are controlled or not. Both quantitative and qualitative research designs are discussed.
1) The document summarizes key aspects of evaluating clinical trials, including types of trials and potential biases.
2) Clinical trials aim to test interventions in a controlled manner to determine safety and effectiveness. Randomized controlled trials (RCTs) are considered the gold standard for limiting biases.
3) However, biases can still influence trials in many ways, such as through selection of participants, administration of interventions, measurement of outcomes, and reporting/publication of results. It is important to critically appraise trials to assess risk of biases.
This document provides an overview of quantitative research methods. It defines quantitative research as a formal, objective, and systematic process used to generate information. The main types of quantitative research described are descriptive research, correlational research, quasi-experimental research, and experimental research. Experimental research aims to determine cause-and-effect relationships through controlled manipulation of variables and random assignment to groups. The steps of the quantitative research process include defining the problem, reviewing literature, identifying variables, collecting and analyzing data, and reporting results.
The document discusses validity and reliability in research. It defines reliability as the consistency of scores from one administration of an instrument to another, and validity as the appropriateness of inferences made from research findings. The document outlines different types of validity evidence including content, criterion, and construct validity. It also discusses threats to internal validity such as subject characteristics, loss of subjects, and location that could influence research outcomes. Methods for achieving validity and reliability are presented, including minimizing threats in experimental research designs.
Three key points about the document:
1. The document discusses correlational research and survey research. It defines correlational research as studying relationships between two or more variables without influencing them. Survey research involves collecting data through questionnaires or interviews to answer questions about populations.
2. The basic steps of correlational research are discussed, including problem selection, sampling, instrumentation, design/procedures, data collection/analysis. Threats to internal validity like subject characteristics and mortality are also covered.
3. The different types of surveys - cross-sectional, longitudinal (trend, cohort, panel), are defined. The key steps in conducting survey research are outlined, such as defining the problem, identifying the population,
1. The document discusses correlational and survey research methods. It defines correlational research as studying relationships between two or more variables without influencing them.
2. The basic steps in correlational research are outlined as problem selection, sampling, instrumentation, design and procedures, data collection, and data analysis and interpretation.
3. Survey research is defined as collecting data using questionnaires or interviews to answer questions about populations. Cross-sectional and longitudinal survey designs are described.
The document discusses different types and properties of triangles. It begins by defining a triangle as a three-sided polygon with three angles and three vertices. It then describes various triangle classifications based on side lengths (scalene, isosceles, equilateral) and angle measures (acute, right, obtuse). Various properties of triangles are outlined, such as angle sum, exterior angles, and relationships between sides and angles. Formulas for calculating perimeter and area of triangles are also provided. The document concludes by presenting theoretical proofs and experimental verifications of several triangle theorems.
Microorganisms are tiny organisms that can only be seen with a microscope. They are classified into five groups: viruses, bacteria, fungi, algae, and protists. Microorganisms are found everywhere and play important roles in environments, as well as in food production and medicine. However, some microorganisms can also cause diseases and food spoilage. There are several methods used to preserve food from microbial spoilage, including drying, cold storage, fermentation, smoking, and salting.
Bagmati Province is one of the seven provinces of Nepal established in 2015. It has the largest population and is the most industrialized province. The province spans 20,300 square kilometers and ranges in elevation from 141 to 7,299 meters. It has a population of over 5.5 million people, most of whom are Hindu and speak Nepali. The province makes up over 40% of Nepal's GDP and has well-developed infrastructure, education, and religious and tourism sites.
tribhuvan University
M.A population Studies
Research methods for population analysis
Data Processing, editing and coding
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Indigenous group of people and social justiceRoji Maharjan
M.A population Studies
principle of demography II
Indigenous Group and social justice
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M.A population Studies
principle od demography II
women and social justice
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Suzanne Lagerweij - Influence Without Power - Why Empathy is Your Best Friend...Suzanne Lagerweij
This is a workshop about communication and collaboration. We will experience how we can analyze the reasons for resistance to change (exercise 1) and practice how to improve our conversation style and be more in control and effective in the way we communicate (exercise 2).
This session will use Dave Gray’s Empathy Mapping, Argyris’ Ladder of Inference and The Four Rs from Agile Conversations (Squirrel and Fredrick).
Abstract:
Let’s talk about powerful conversations! We all know how to lead a constructive conversation, right? Then why is it so difficult to have those conversations with people at work, especially those in powerful positions that show resistance to change?
Learning to control and direct conversations takes understanding and practice.
We can combine our innate empathy with our analytical skills to gain a deeper understanding of complex situations at work. Join this session to learn how to prepare for difficult conversations and how to improve our agile conversations in order to be more influential without power. We will use Dave Gray’s Empathy Mapping, Argyris’ Ladder of Inference and The Four Rs from Agile Conversations (Squirrel and Fredrick).
In the session you will experience how preparing and reflecting on your conversation can help you be more influential at work. You will learn how to communicate more effectively with the people needed to achieve positive change. You will leave with a self-revised version of a difficult conversation and a practical model to use when you get back to work.
Come learn more on how to become a real influencer!
This presentation by Yong Lim, Professor of Economic Law at Seoul National University School of Law, was made during the discussion “Artificial Intelligence, Data and Competition” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/aicomp.
This presentation was uploaded with the author’s consent.
This presentation by Thibault Schrepel, Associate Professor of Law at Vrije Universiteit Amsterdam University, was made during the discussion “Artificial Intelligence, Data and Competition” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/aicomp.
This presentation was uploaded with the author’s consent.
This presentation by Juraj Čorba, Chair of OECD Working Party on Artificial Intelligence Governance (AIGO), was made during the discussion “Artificial Intelligence, Data and Competition” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/aicomp.
This presentation was uploaded with the author’s consent.
This presentation by Nathaniel Lane, Associate Professor in Economics at Oxford University, was made during the discussion “Pro-competitive Industrial Policy” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/pcip.
This presentation was uploaded with the author’s consent.
This presentation by Professor Alex Robson, Deputy Chair of Australia’s Productivity Commission, was made during the discussion “Competition and Regulation in Professions and Occupations” held at the 77th meeting of the OECD Working Party No. 2 on Competition and Regulation on 10 June 2024. More papers and presentations on the topic can be found at oe.cd/crps.
This presentation was uploaded with the author’s consent.
XP 2024 presentation: A New Look to Leadershipsamililja
Presentation slides from XP2024 conference, Bolzano IT. The slides describe a new view to leadership and combines it with anthro-complexity (aka cynefin).
Mastering the Concepts Tested in the Databricks Certified Data Engineer Assoc...SkillCertProExams
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This presentation by OECD, OECD Secretariat, was made during the discussion “Competition and Regulation in Professions and Occupations” held at the 77th meeting of the OECD Working Party No. 2 on Competition and Regulation on 10 June 2024. More papers and presentations on the topic can be found at oe.cd/crps.
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Collapsing Narratives: Exploring Non-Linearity • a micro report by Rosie WellsRosie Wells
Insight: In a landscape where traditional narrative structures are giving way to fragmented and non-linear forms of storytelling, there lies immense potential for creativity and exploration.
'Collapsing Narratives: Exploring Non-Linearity' is a micro report from Rosie Wells.
Rosie Wells is an Arts & Cultural Strategist uniquely positioned at the intersection of grassroots and mainstream storytelling.
Their work is focused on developing meaningful and lasting connections that can drive social change.
Please download this presentation to enjoy the hyperlinks!
This presentation by OECD, OECD Secretariat, was made during the discussion “Artificial Intelligence, Data and Competition” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/aicomp.
This presentation was uploaded with the author’s consent.
Updated diagnosis. Cause and treatment of hypothyroidism
Threats to validity
1. Validity and Threats to
Validity
Presented By: Roji maharjan
Masters of Arts (T.U.)
Population Studies
Padma Kanya Multiple Campus
2. Objectives:
• To define validity
• To explain Methods of validity test along with its threats
3. Validity
• Validity is the extent to which a concept, conclusion or measurement is
well-founded, accurately measuring what it’s supposed to and
corresponds to real world.
• The term Validity means truth.
• Validity refers to the degree to which a test measure what is
claims to measure.
• Validity means to measure with reasonable degree of Accuracy.
4. Methods of validity
1. External Validity:
-External validity is related to generalizing.
-It is the degree to which the conclusions in study would hold for
other persons in other places and at other times.
-The variables used in the study are similar to those aspects as they
exist in the larger population.
-It occurs when the causal relationship discovered can be
generalized to other people, time and contexts.
5. Threats to External validity:
• Selection Bias: The sample is not representative of the population.
• History: An unrelated event influences the outcomes.
• Experimenter effect: The characteristics or behaviors of the
experimenter unintentionally influence the outcomes.
• Hawthorne effect: The tendency for participants to change their
behaviors simply because they know they are being studied.
• Testing effect: The administration of a pre-test or post-test affects
the outcomes.
• Aptitude-treatment: Interactions between characteristics of the
group and individual variables together influence the dependent
variable.
• Situation effect: Factors like the setting, time of day, location,
researchers’ characteristics, etc. limit generalizability of the
findings.
6. 2.Internal Validity
• It refers to the extent to which the results obtained in a research
study are a function of the variables that systematically
manipulated, measured, and observed in the study.
• It is the extent to which shows a cause-and-effect relationship
established in a study cannot be explained by other factors.
• It is the approximate truth about inferences regarding cause-effect
or causal relationships.
7. Threats To internal validity:
• History: the occurrence of events that could alter the outcome or the results.
• Maturation: any changes that occur in the subjects during the course of the
study that are not part of the study and that might affect the results of the
study.
• Instrumentation: concerned with the effects on the outcome of a study of the
inconsistent use of a measurement instrument.
• Testing: the possible effects of a pre-test on the performance of participants
in a study on the post-test.
• Statistical Regression: the tendency of extreme scores to move (or regress)
toward the mean score on subsequent retesting.
• Mortality: the loss of subjects from a study due to their initial non-availability or
subsequent withdrawal from the study.
• Selection: possibility that groups in a study may possess different characteristics
and that those differences may affect the results.
8. Construct Validity
• It refers to the degree to which inferences can legitimately be made
from the operationalizations in study to the theoretical constructs on
which those operationalizations were based.
• The quality of choices about the particular forms of the independent
and dependent variables.
9. Threats To Construct Validity:
• Mono-Operation Bias: it pertains to the independent variable, cause,
program or treatment in study – it does not pertain to measures or
outcome.
• Mono-Method Bias: it refers to your measures or observations, not to
your programs or causes.
• Interaction of Different Treatments:
• Interaction of Testing and Treatment.
• Restricted Generalizability Across Constructs.
• Confounding Constructs and Levels of Constructs.
• The “Social” Threats
• Inadequate Preoperational Explication of Constructs.
• Hypothesis Guessing
10. 4.Conclusion Validity
• Conclusion validity is the degree to which conclusions we reach
about relationships in our data are reasonable.
• It is relevant whenever we are trying to decide if there is a
relationship in our observations.
• It is the degree to which the conclusion we reach is credible or
believable.
11. Threats to conclusion validity:
A threat to conclusion validity is a factor that can lead you to reach
an incorrect conclusion about a relationship in your observations.
• low reliability of measures
• poor reliability of treatment implementation
• random irrelevancies in the setting
• random heterogeneity of respondents.
• low statistical power
• fishing and the error rate problem
• violated assumptions of statistical tests