1368 triangulation summary
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Triangulation is a method that uses multiple data sources to analyze programs and policies. It involves planning, data collection, analysis, and communicating results. Key steps include identifying questions, gathering different types of data, analyzing trends across data sets, developing and checking hypotheses, and generating recommendations. The process aims to improve decision making by demonstrating program impacts and areas for improvement.
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This document discusses different types of triangulation that can be used in research to increase validity. It describes data triangulation as using multiple data sources like increasing data collection sites, participants, and quotations. Investigator triangulation involves using multiple researchers to analyze data. Theory triangulation examines the same problem through different theoretical lenses. Methodological triangulation uses different data collection methods like interviews and observations. Environmental triangulation varies environmental factors like location or time of day to see if findings remain the same. The document asserts that triangulation provides a more valid and multi-dimensional understanding of research issues.
Triangulation
This document discusses different types of triangulation that can be used in research to increase validity and credibility. It defines triangulation as using multiple methods, data sources, investigators, theories or research contexts to check results. Specifically, it outlines data triangulation, investigator triangulation, theory triangulation, methodological triangulation and environmental triangulation. For each type, it provides an example of how it could be applied in practice to strengthen research findings.
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This document discusses the concept of triangulation as it relates to research methods. It defines triangulation as using multiple methods, data sources, investigators, theories or research contexts to check results. The main purposes of triangulation are to increase the validity and credibility of research findings. It then describes five main types of triangulation: data, investigator, theory, methodological, and environmental triangulation.
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Triangulation refers to using multiple research methods, data sources, investigators, or theoretical perspectives to study a phenomenon and increase the validity and reliability of research findings. It involves looking at something from several different angles to gain a more complete understanding. While triangulation aims to overcome bias and validity issues, it is most effective when methods, data sources, and perspectives share the same underlying assumptions and are analyzed consistently within a single paradigm or theoretical framework. Simply combining qualitative and quantitative data or perspectives risks introducing inconsistencies without a shared foundation.
Triangulation ppt modified
Triangulation is a method used in research to validate findings through cross-verification from multiple sources. It involves using multiple data sources, researchers, theoretical perspectives, or research methods. The main purpose of triangulation is to increase the credibility and validity of research results. There are four main types of triangulation: data triangulation, investigator triangulation, theory triangulation, and methodological triangulation. Triangulation helps provide a more comprehensive understanding of the phenomena under study but can be time consuming and expensive.
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Triangulation is a method used in research to validate findings through cross-verification from multiple sources. It involves using multiple data sources, researchers, theoretical perspectives, or research methods. The main purpose of triangulation is to increase the credibility and validity of research results. There are four main types of triangulation: data triangulation, investigator triangulation, theory triangulation, and methodological triangulation. Triangulation helps provide a more comprehensive understanding of the phenomena under study but can be time consuming and expensive.
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1. Defining quantitative research and comparing it to qualitative research. Quantitative research relies on mathematical/statistical models and analysis of numeric data.
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Importance of data collection:
Helps us search for answers and resolutions
Facilitates and improve decision-making processes and the quality of the decisions made.
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Outline the four steps in the data collection process.
Explain why it is so important to be systematic in collecting data.
Solution
Step 1: Identify issues and/or opportunities for collecting dataordata collection goals
what problem are you trying to solve by collecting this data?
Step 2:Develop operational definitions and procedures.
Here we need to be very clear as to what we are measuring, how it is to be measured, and who is
to measure it. Often times we will employ sampling in which case we need to define a sampling
plan.
. Who will the data be collected about?
. Who will the group of interest be compared to?
. What locations or geographical areas will the data be gathered from?
. What categories will be used to identify the group of interest and comparator group?
Step 3 : How should data be collected and What sources of data should be used to collect
information?
There are several methods of collecting data: online-surveys, phone interviews, focus groups and
yes, even dreaded handwritten surveys. Each type possesses its own advantages and
disadvantages. Whichever method you use, there are bound to be obstacles to overcome along
the way.
What sources of data should be used to collect information?
Pre-existing or official data
Survey data
Interviews and focus groups
Observed data
. Two types of data are used in any field of research: qualitative and quantitative.
Qualitative data:
Typically, data is called “qualitative” if it is in the form of words, but may also include any
information that is not numerical in form, such as photographs, videos and sound recordings.
Qualitative methods are aimed at describing a specific context, event, people or relationship in a
broad contextual way, by trying to understand the underlying reasons for behaviour, thoughts
and feelings.
Common qualitative research methods include observation, one-on-one interviews, focus groups
and intensive case studies
Quantitative data:
Typically, data is called “quantitative” if it is in the form of numbers.
A quantitative approach can be used to count events or the number of people who represent a
particular background.
Common quantitative tools include surveys, questionnaires and statistical data (such as Statistics
Canada census information).
It is important to note that all quantitative data is based on qualitative judgment. In other words,
numbers cannot be interpreted by themselves, without understanding the assumptions that
underlie them.
A good research effort involves the use of both types. Both approaches, while distinct, can
overlap and rely on the other to produce meaningful data, analysis and results.
Step 4 : Analyze and interpret data and Act on results
Explaining the technical steps involved in analyzing and interpreting data is beyond the scope of
this guide. An organization will have to determine whether it has the internal capacity and
expertise to analyze and interpret data itself, or whether it will need the help of an external
consultant.
. A summa.
Highlights from ExL Pharma's 12th Investigator Initiated Trials
- ExLPharma holds annual conferences on investigator-initiated trials (IITs) to discuss governance models, planning, operations, and the role of medical science liaisons (MSLs).
- Key topics included developing a review committee and charter, strategic planning documents, budgeting, standard operating procedures, and metrics to measure program success.
- The role of MSLs in IITs is to provide scientific feedback, study information, and liaise across functions like medical information and clinical development to support investigators.
- Prioritizing IITs involves aligning them with product strategies and evaluating proposals based on strategic fit, scientific design, and investigator/site capabilities.
Lecture on marketing research.
Marketing research that is the foundation of a successful marketing plan/campaign.
Why marketing research is important
If you need a copy of the Power point presentation email your request @ dngrtz2000@hotmail.com, will send you your copy immediately.
Strategic Development and Expansion of the Clinical Trials Infrastructure
Strategic Development and Expansion of the Clinical Trials InfrastructureOffice of Research Information Services @ the University of Washington
The goal is to improve the quality of the clinical trials and increase the number of clinical trials.MethodsofDataCollection.pdf
This document discusses different methods of data collection. It defines data collection as the process of systematically gathering and measuring information on variables of interest in order to answer research questions and test hypotheses. The two main types of data are qualitative and quantitative. Qualitative data is non-numerical, descriptive data often in the form of words, while quantitative data is numerical and can be mathematically computed. Common qualitative methods include interviews and focus groups, while quantitative methods include surveys, experiments, and observational studies. The document also discusses mixed methods research, which combines qualitative and quantitative approaches.
Philosophical foundations of education
This document discusses the policy evaluation process. It begins by defining policy evaluation as determining the effectiveness and efficiency of government policies and identifying areas for change and improvement. It then outlines the main stages of the policy process and lists four standards for conducting policy evaluations: utility, feasibility, propriety, and accuracy. The two main types of evaluation are formative and summative. Formative evaluation aims to improve a project during implementation while summative evaluation assesses outcomes. The key steps in the policy evaluation process are defined as: defining purpose and scope, specifying the evaluation design, creating a data collection plan, collecting and analyzing data, drawing conclusions, and providing feedback for improvement.
Stakeholder Engagement
The Stakeholder Engagement tool helps ensure that the appropriate stakeholders in decision processes have been identified and involved.
Tool: https://www.cpc.unc.edu/measure/publications/ms-11-46-e
Webinar Recording: http://universityofnc.adobeconnect.com/p99y8bhnosx/
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- 3. Triangulation Process Communicating Results Planning Triangulation Conducting Triangulation