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e-Source Book
Appropriate Research Methods
'Science' in the Social Sciences
Theory Development
Sample Surveys
Social Survey Data Collection
Administrative Data Systems
Observational Studies
Qualitative Methods
Conversation Analysis
Software and Qualitative Analysis
Clinical Trials
Cluster Unit Randomized Trials
Multilevel Modeling
Patient-Reported Outcomes
About OBSSR
OBSSR Overview
Contact Us
Objectives of the Website
e-Learning for Behavioral & Social Sciences Research
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Appropriate Research Methods
1. Learning Objectives
2. Introduction
3. Different Methods
4. What's Wrong
5. Where to Now
6. Appropriate Methods
7. Danger in Dichotomizing
8. The Essentials
9. From Description to Explanation
10. Understanding What Works
11. Finding Harmony
12. Summary
13. References
14. Author Biography
'Science' in the Social Sciences
1. Learning Objectives
2. Introduction
3. Statistical Data
4. Causal Reasoning
5. Psychiatric Epidemiology
6. Positivism
7. Probabilistic Reasoning
8. Purposes of Social Research
9. 'Science' in the Social Sciences
10. Summary
11. Glossary
12. References
13. Author Biography
Theory Development
1. Learning Objectives
2. Introduction
3. Causal Complexity
4. Prediction vs. Explanation
5. Meaning and Background
6. Common Sense
7. Who Believes What?
8. Understanding and Interpretation
9. Two Approaches
10. Mechanisms
11. Theories and Systematization
12. Determining Real Causes
13. Confounding
14. Problems with Causal Models
15. Summary
16. References
17. Author Biography
Sample Surveys
1. Learning Objectives
2. Introduction
3. Defining Objectives
4. Total Survey Error
5. Designing a Sample
6. Developing a Survey Instrument
7. Collecting Data
8. Preparing for Analysis
9. Calculating Survey Weights
10. Calculating Estimates
11. Reporting Results
12. Resources
13. References
14. Author Biography
Social Survey Data Collection
1. Learning Objectives
2. Introduction
3. Recruitment
4. Interviewer Training
5. Continuous Interviewer Learning
6. Monitoring Interviewers in the Field
7. Summary
8. References
9. Author Biography
Administrative Data Systems
1. Learning Objectives
2. Introduction
3. History
4. Features
5. Accessing Data
6. Advantages and Disadvantages
7. Illustrations
8. Summary
9. Resources
10. References
11. Author Biography
Observational Studies
1. Learning Objectives
2. Introduction
3. Descriptive Validity
4. External Validity
5. Construct Validity
6. Measurement Validity
7. Measurement Reliability
8. Formal Representation
9. Internal Validity
10. Statistical Conclusion Validity
11. Summary
12. References
13. Author Biography
Qualitative Methods
1. Learning Objectives
2. Introduction
3. Observation
4. Interviews and Focus Groups
5. Documents
6. Visual Data
7. Multiple Methods
8. Credibility
9. Summary
10. Resources
11. Glossary
12. Transcription Symbols
13. References
14. Author Biography
Conversation Analysis
1. Learning Objectives
2. Introduction
3. Basic Principles of CA
4. CA and the Medical Encounter
5. CA in Action
6. Interactions and Outcomes
7. Unmet Concerns
8. Prescribing Decisions
9. CA as Intervention
10. Transcription Symbols
11. Summary
12. References
13. Author Biography
Software and Qualitative Analysis
1. Learning Objectives
2. Introduction
3. Conducting Rigorous Qualitative Research
4. The Qualitative Research Process
5. Logic of Qualitative Research
6. The First Stage
7. Drawing and Verifying Conclusions
8. The Role of Computers
9. Software
10. Choosing QDA Software
11. Summary
12. Resources
13. References
14. Author Biography
Clinical Trials
1. Learning Objectives
2. Introduction
3. Classification
4. Endpoints
5. Design Issues
6. Erroneous Trial Results
7. Statistics
8. Summary
9. Glossary
10. References
11. Author Biographies
Cluster Unit Randomized Trials
1. Learning Objectives
2. Introduction
3. Statistical Implications
4. Common Designs
5. Pair-Matching
6. Unit of Inference
7. Sample Size Assessment
8. Factors Influencing Power
9. Cluster Level Replication
10. CRTs and Informed Consent
11. Cluster vs. Individual Level Analysis
12. Perils of Subsampling
13. Other Perils
14. Analyses at the Individual Level
15. Interim Analyses
16. Cohort vs. Cross-sectional Designs
17. Reporting
18. Appendix
19. Summary
20. References
21. Author Biography
Multilevel Modeling
1. Learning Objectives
2. Introduction
3. Multilevel Framework
4. Multilevel Methods and Analyses
5. Desiderata for Multilevel Research
6. Multilevel Data Structures
7. Levels and Variables
8. A Graphical Introduction
9. Specifying and Interpreting Models
10. Modeling Contextual Effects
11. Multiple Spatial Contexts
12. Multilevel Residual Mapping
13. Parameter Estimation
14. Non-linear Multilevel Models
15. Spatially Aggregated Data
16. Interpreting a Multilevel Model
17. Power and Sample Size
18. Summary
19. References
20. Author Biography
Patient-Reported Outcomes
1. Learning Objectives
2. Introduction
3. Reasons to Measure PROs
4. Individualizing QOL Measures
5. Terminology of PROs
6. Label What We Measure
7. Validity and PROs
8. Interpretability
9. Types of Measures
10. Applications
11. Summary
12. Resources
13. References
14. Author Biographies
Tables
Figures
Exercises
Examples
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Office of Behavioral and Social Sciences Research
Department of Health and Human Services
National Institutes of Health
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