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Research Design Types and Logic: Enhancing Project Precision

Review last week's student answers, differentiate between research designs, analyze gun ownership measurements, explore Runkel & McGrath's criteria, and practice concepts using real examples. Understand how research designs differ from statistical analyses.

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Research Design Types and Logic: Enhancing Project Precision

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  1. Agenda • Review of Last week • Learn about types of Research designs • How are they different from each other? From other things? • Applying what you learned with in-class exercises • Using what you learned toward your projects

  2. Review: Students answer • List all the ways used to measure gun ownership in the article • For each way, identify whether used as predictor or criterion variable • Describe (with a diagram) the hypotheses • For each, identify the kind of hypothesis • Explain (with a diagram) the logic behind the hypotheses

  3. Types of Research Designs

  4. Typical Examples of Research Designs • Field Studies • Laboratory Experiments

  5. Two criteria differentiating research designs • The obtrusiveness of the operations they use • Specificity of the Systems they study

  6. Runkel & McGrath, 1972 Obtrusive Operations Lab Experiments Unobtrusive Operations Field Studies Particular Behavior Systems Universal Behavior Systems

  7. Example of a Laboratory Experiment

  8. Example of a field Study • Conference Board study • What is it particular to? • In what way is it unobtrusive?

  9. Adding a third criterion to differentiate research designs • Degree to which settings are natural to the behavior being studied • The obtrusiveness of the operations they use • Specificity of the Systems they study

  10. Universal Behavior Systems Obtrusive Operations Lab Experiments Particular Behavior Systems Field Experiments Field Studies Unobtrusive Operations Natural Settings Contrived Setting Runkel & McGrath, 1972

  11. Adding a fourth criterion to differentiate research designs • Precision of measurement • Degree to which settings are natural to the behavior being studied • The obtrusiveness of the operations they use • Specificity of the Systems they study

  12. Maximum Precision Obtrusive Operations Lab Experiments Experimental Simulations Max Context Field Experiments Field Studies Unobtrusive Operations Natural Settings Contrived Setting Runkel & McGrath, 1972

  13. Examples from Guns & Crime Article • Field Study • Handgun magazine sales & gun related deaths

  14. Examples from IRE2002Y Instructor’s Research • Experimental Simulation • Radhakrishnan (1996) Dissertation study • Field Experiment • Radhakrishnan Writing Study (2006)

  15. Example from Guns & Crime Article • Field Experiment • Gun magazine sales in Year 1 related to homicide rate in Year 2 • Homicide rate in Year 1not related to gun magazine sales in Year 2

  16. Practice concepts learned so far with Guns & Crime Article • Which design establishes the causal relationship with more precision? Why/how?

  17. Adding a fifth criterion differentiating research designs • Degree to which to the behavior being studied is independent of the setting • Precision of measurement • Degree to which settings are natural to the behavior being studied • The obtrusiveness of the operations they use • Specificity of the Systems they study

  18. Obtrusive Operations Lab Experiments Field Experiments Sample Surveys Field Studies Unobtrusive Operations Setting Independent Setting Dependent Runkel & McGrath, 1972

  19. Examples • Sample Survey • Gallup Polls • Spector, Radhakrishan et al. (2001) • Schimmack, Radhakrishnan et al. (2002) • Field Study • Conference Board Studies

  20. A sixth criterion differentiating research designs • Degree to which to they maximize generality of behaviors studied by • Large samples • Multiple variables • Degree to which to the behavior being studied is independent of the setting • Precision of measurement • Degree to which settings are natural to the behavior being studied • The obtrusiveness of the operations they use • Specificity of the Systems they study

  21. Runkel & McGrath, 1972 Maximum Precision Obtrusive Operations Minimum Generality Experimental Simulations Lab Experiments Field Experiments Sample Surveys Formal Theory Unobtrusive Operations Maximum Generality Universal Behavior Systems Particular Behavior Systems

  22. Examining all criteria differentiating research designs simultaneously

  23. Runkel & McGrath, 1972 Contrived Settings Maximum Precision Obtrusive Operations Experimental Simulations Lab Experiments Field Experiments Setting Independent Natural Settings Sample Surveys Field Studies Maximum Context Computer Simulations Formal Theory Unobtrusive Operations Maximum Generality Behavior not measured Universal Behavior Systems Particular Behavior Systems

  24. Review & Next Steps… • Types of research designs • How research designs are different from • Types of data analyses • Types of data

  25. Research Designs vs. Statistical Analyses • Research design= way of collecting data • Statistical Analysis =way of analyzing data

  26. Examples of Statistical Analyses • Means • Frequencies • Correlations • Regression • ANOVA

  27. Research Designs vs. Statistical Analyses • Data collected in field studies or sample surveys lend themselves to correlational analyses • Sometimes, the term “correlational method” is (confusingly) used to imply field study or a sample survey in contrast to the experimental method that is used to imply laboratory or field experiments • There is no such thing as experimental analyses

  28. Meta-analysis: An example of a statistical analysis • A way of analysing data collected across multiple settings & samples to estimate overall size of relation between variables • Helps in • Developing theory, identifying research needs, • Establishing validity/effectiveness of tools (e.g., teaching writing) • Replace sample surveys • Better than qualitative literature reviews

  29. Meta-analyses vs. sample surveys • Sample Survey • A way of collecting data • Meta analyses • A way of analysing data • Can involve sample surveys, field studies, lab experiments

  30. Research Designs vs. Type of data • Examples of Qualitative Data: • Themes from Interview transcripts • Themes from focus group transcripts • Some kinds of observational/archival data • Examples of Quantitative Data: • What are examples of quantitative data in the guns & crime article

  31. Research Designs vs. Type of data • Quantitative & qualitative data can be collected in all research designs

  32. Review & Next steps • Types of research designs • How research designs are different from • Types of data analyses • Types of data • Applying what you learned

  33. Applying what you learned: Student do exercises & answer orally • What is the type of research design used in each study description in handouts from last week

  34. Review & Next steps • Research designs • Applying what you learned • Using what you learned in your projects

  35. Choose a Research Design for your project that • Adequately test the hypothesis • Is efficient in using available resources • Rejects/retains the hypothesis via statistical means • Can statistically control for some extraneous factors • Ensures that results are generalizable

  36. Choose a Research Designthat adequately tests the hypothesis • Hypotheses determine participants, variables measured & data analysis methods • Students answer orally: What are some (tentative) hypotheses tested in your projects?

  37. Choose a design that is efficient in using available resources • Resources: time, material resources, expertise • Students answer orally: What are possible designs you can use in student projects?

  38. Choose a Research Design that can reject/retain the hypothesis via statistical analyses • Need reliable measures — Future readings & lectures • Need large enough sample to detect true effect & avoid errors-- Future readings & lectures

  39. Choose a Research Design that can control for some extraneous variables • Control=Eliminate extraneous variables that can affect dependent variables increases confidence in cause-effect conclusion • Depends on type of design

  40. Controlling Extraneous Variables in Experimental Designs • Random Assignment • Distributing extraneous variable across groups randomly • Matching Groups • Spreading the extraneous variable across groups via systematic assignment • Less effective than random assignment (p.148 Sekaran) • Control Group • Group that receives no manipulation

  41. Controlling Extraneous Variables • Extraneous variables are reliably measured and effects are statistically controlled • Future lectures on Power & Statistical Analyses • Typically done in • Field studies • Field Experiments • Sample surveys • Students give examples from Guns & Crime articles

  42. Choose a design that gives generalizable results • Generalizable=Replicate to other samples and other contexts • Random selection of participants • Large number of participants • Large number of contexts • E.g., meta-analysis

  43. Ensure your project design • Adequately test the hypothesis • Is efficient in using available resources • Rejects/retains the hypothesis via statistical means • Can statistically control for some extraneous factors • Ensures that results are generalizable

  44. What you learned today • Types of research designs • How research designs are different from • Types of data analyses • Types of data

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