Research design


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Research design

  1. 1. Research Design <ul><li>Andrew Martin </li></ul><ul><li>PS 372 -- University of Kentucky </li></ul>
  2. 2. What is research design? <ul><li>Research design is a plan that shows how a researcher intends to study an empirical question. </li></ul><ul><li>Choice of research design depends on a number of factors. </li></ul>
  3. 3. Research Designs should ... <ul><li>(1) Establish a relationship between two or more variables. (Comparison)‏ </li></ul><ul><li>(2) Demonstrate the results are generally true in the real world. (Generalizability)‏ </li></ul><ul><li>(3) Reveal whether one phenomenon precedes another in time. (Manipulation)‏ </li></ul><ul><li>(4) Eliminate as many alternative explanations as possible. (Control)‏ </li></ul>
  4. 4. Causal vs. Spurious Relationships <ul><li>A causal relationship is a connection between two variables that occurs because one produces, or brings about, the other with complete or great regularity. </li></ul><ul><li>The independent variable is the cause, the dependent variable is the effect. </li></ul>
  5. 5. Causal vs. Spurious Relationships <ul><li>A spurious relationship occurs when the relationship between two variables appears to be valid but is actually explained by variables other than those stated in the hypothesis. </li></ul>
  6. 6. <ul><li>JRM 124 </li></ul>
  7. 7. Downs Voter Paradox (1957)‏ <ul><li>In An Economic Theory of Democracy, Anthony Downs concludes that voting is an irrational act in most instances. </li></ul><ul><li>Reward = Probability your vote changes election outcome * benefits - costs </li></ul><ul><li>R = PB - C </li></ul>
  8. 8. Research Design and Causal Inferences <ul><li>To explain why phenomena are connected, we must know why they are connected, not simply that they are associated. </li></ul>
  9. 9. Riker and Ordeshook (1968)‏ <ul><li>Reformulated model, suggesting Downs’ model omitted an important component of an individual’s choice to vote, the intangible benefits. </li></ul><ul><li>Thus, the model becomes: R = PB - C + D </li></ul><ul><li>D represents non-instrumental or expressive benefits. </li></ul>
  10. 10. Research Design and Causal Inferences <ul><li>Covariation . The research must demonstrate that the alleged cause (X) does in fact covary with the supposed effect (Y). </li></ul><ul><li>Time order. The research must show that the cause preceded the effect. </li></ul><ul><li>Eliminates alternatives . All possible joint causes of X and Y must be eliminated. </li></ul>
  11. 11. <ul><li>JRM 125 </li></ul>
  12. 12. <ul><li>JRM 126 </li></ul>
  13. 13. Research Designs <ul><li>Four major approaches in the social sciences: </li></ul><ul><li>Experimental design </li></ul><ul><li>Quasi-experimental design </li></ul><ul><li>Cross-sectional design </li></ul><ul><li>Pre-Experimental design </li></ul>
  14. 14. Experiments <ul><li>Experiments allow the researcher to control exposure to an experimental variable (or independent variable). </li></ul><ul><li>Theoretically, this allows researchers to make causal inferences with greater confidence than non-experimental approaches. </li></ul>
  15. 15. Classical Experimental Design <ul><li>Classical experimental design involves an experiment with the random assignment of subjects to experimental and control groups with a pre-test and a post-test. </li></ul>
  16. 16. Classical Experimental Design <ul><li>Establishes an experimental group and a control group. </li></ul><ul><li>Each subject is randomly assigned to one group or the other. </li></ul><ul><li>The researcher controls the administration or introduction of the experimental treatment. </li></ul>
  17. 17. Classical Experimental Design <ul><li>The researcher establishes and measures a dependent variable both before and after the experimental variable is introduced. </li></ul><ul><li>The experimenter controls the environment -- that is, the time, location and other physical aspects of the of the experiment. </li></ul>
  18. 18. <ul><li>JRM 129 </li></ul>
  19. 19. <ul><li>NN 91 </li></ul>
  20. 20. Internal Validity <ul><li>Internal validity constitutes the ability to show that manipulation or variation of the independent variable actually causes the dependent variable to change. </li></ul>
  21. 21. Internal Validity <ul><li>Internal validity is directly related to the control component of research design. </li></ul><ul><li>Random assignment of participants helps guard against this, but sometimes this is not ethical or practical. </li></ul><ul><li>Extrinsic factors can sometimes produce differences between experimental and control groups. </li></ul>
  22. 22. Internal Validity <ul><li>Extrinsic factors produce differences in the two groups prior to the research operation. </li></ul><ul><li>When this happens, it is difficult to distinguish selection effects from effects of the independent variable. </li></ul><ul><li>This causes selection bias, and it threatens a study’s internal validity. </li></ul>
  23. 23. Internal Validity <ul><li>Intrinsic factors include changes to individuals or units studies during the study period. </li></ul>
  24. 24. Intrinsic Factors <ul><li>History </li></ul><ul><li>Maturation </li></ul><ul><li>Experiment mortality </li></ul><ul><li>Instrumentation </li></ul><ul><li>Testing </li></ul><ul><li>Regression artifact </li></ul><ul><li>Interactions with selection </li></ul>
  25. 25. Intrinsic Factors Nachmias-Nachmias (2000)‏ <ul><li>History refers to all events that occurred during the time of the study that might affect the individuals studied and provide a rival explanation for the change in the dependent variable. </li></ul><ul><li>Ex: Financial crisis in government during the time of the experiment. </li></ul>
  26. 26. Intrinsic Factors Nachmias-Nachmias (2000)‏ <ul><li>Maturation involves biological, psychological or social processes that produce changes in individuals or units studied with the passage of time. </li></ul><ul><li>Ex: Test scores and teaching methods. Perhaps the students just became older and wiser independently of teaching method. </li></ul>
  27. 27. Intrinsic Factors Nachmias-Nachmias (2000)‏ <ul><li>Experimental mortality refers to dropout problems that prevent the researcher from obtaining complete information on all cases. </li></ul><ul><li>Ex: Studying the effect of media on prejudice, and most dropouts were prejudiced individuals. </li></ul>
  28. 28. Intrinsic Factors Nachmias-Nachmias (2000)‏ <ul><li>Instrumentation designates changes in the measuring instruments between the pre-test and post-test. </li></ul><ul><li>Ex: Changing criteria for evaluating psychological tests. </li></ul>
  29. 29. Intrinsic Factors Nachmias-Nachmias (2000)‏ <ul><li>Testing the possible reactivity of measurement is a major problem in social science research. The process of testing may change the phenomena being measured. </li></ul><ul><li>Ex: People aware of the purpose of the survey; taking intelligence tests often </li></ul>
  30. 30. Intrinsic Factors Nachmias-Nachmias (2000)‏ <ul><li>Sometimes selection factors and intrinsic factors interact. </li></ul><ul><li>The most common are selection-history and selection-maturation . </li></ul>
  31. 31. Procedures of Control Nachmias-Nachmias (2000)‏ <ul><li>Matching </li></ul><ul><li>Randomization </li></ul><ul><li>The Control Group </li></ul>
  32. 32. Matching Nachmias-Nachmias (2000)‏ <ul><li>Matching is a way of equating the experimental and control groups on extrinsic factors known to be related to the research project. </li></ul>
  33. 33. Matching Nachmias-Nachmias (2000)‏ <ul><li>Precision matching, for each case in the group, another case with identical characteristics is selected for the control group. </li></ul>
  34. 34. <ul><li>NN 98 </li></ul>
  35. 35. Matching Nachmias-Nachmias (2000)‏ <ul><li>Frequency distribution looks at central characteristics of the two groups rather than on-on-one matching. </li></ul><ul><li>Frequency distribution is a more efficient alternative. </li></ul>
  36. 36. <ul><li>NN 99 </li></ul>
  37. 37. Randomization Nachmias-Nachmias (2000)‏ <ul><li>Randomization is a method of control that helps to offset the confounding effects of known and unknown factors by randomly assigning cases to experimental and control groups. </li></ul><ul><li>Can be accomplished by flipping a coin, using a table of random digits or any other method that ensure each case has an equal probability of being chosen. </li></ul>
  38. 38. External Validity Nachmias-Nachmias (2000)‏ <ul><li>External validity is the extent to which the research findings can be generalized to larger populations and applied to different settings. </li></ul><ul><li>The two main components of external validity are representativeness of the sample and reactive arrangements in the research process. </li></ul>
  39. 39. External Validity Nachmias-Nachmias (2000)‏ <ul><li>Reactive arrangements can compromise the experimental setting or situation if they do not reflect the natural setting or situation about which researchers wish to generalize. </li></ul><ul><li>The way the study is conducted could impact its outcome. Ex: Surveys, subject response and question wording. </li></ul>