Experimentation

1. Experimentation Chapter 14 Cooper and Schindler

2. What is Experimentation? • Causal method • Allow the researcher to alter systematically the variables of interest and observe what changes follow • Experiments are studies involving intervention by the researcher beyond that requires for measurement • The researcher manipulates the independent variable or explanatory variable and then observes whether the hypothesized dependent variable is affected by the intervention

3. Advantages • The researcher’s ability to manipulate the independent variable • Contamination from extraneous variables can be controlled more effectively than in other design • The convenience and cost of experimentation are superior to other methods • Assemble combinations of variables for testing

4. Disadvantages • The artificiality of the laboratory • Generalization from nonprobability samples can pose problems despite random assignment • Many applications of experimentation far outrun the budgets • Experimentation is most effectively targeted at problems of the present or immediate future • Ethical problems

5. Conducting An Experiment • Select relevant variables • Specify the level(s) of the treatment • Control the experimental environment • Select and assign the subjects • Pilot-test, revise, and test • Analyze the data

6. Selecting Relevant Variables • Translate an amorphous problem into the question or hypothesis that best states the objectives of the research • Investigative questions and additional hypotheses can be created to address specific facets of the study or data that need to be gathered

7. Specifying the Levels of Treatment • The treatment levels of the independent variable are the distinctions the researcher makes between different aspects of the treatment condition • A control group could provide a base level for comparison • Experimental group

8. Ways to Assign Subjects • Random Assignment • Matching Assignment • Quota matrix

9. Controlling the Experimental Environment • The need for control • Extraneous variables have potential for distorting the effect of the treatment on the dependent variable and must be controlled or eliminated • Environmental control • Holding constant the physical environment of the experiment • Blind • Subjects do not know they are receiving the experimental treatment • Double blind • The experimenters do not know they are giving the treatment to the experimental group or to the control

10. Choosing the Experimental Design • Preexperimental designs • True experimental designs • Field experiments

11. Preexperimental Designs • One-shot case study • One-group pretest-posttest design • Static group comparison

12. True Experimental Designs • Pretest-posttest control group design • Posttest-only control group design

13. Operational Extensions of True Designs • Completely randomized designs • Randomized block design • Latin square • Factorial design • Covariance analysis

14. Field Experiments: Quasi- or Semi-Experiments • Non Equivalent Control Group Design • Separate Sample Pretest-Posttest Design • Group Time Series Design

15. Selecting and Assigning Subjects • The subjects selected for the experiment should be representative of the population • Random assignment to the groups is required to make the groups as comparable as possible with respect to the dependent variable • When it is not possible to randomly assign subjects to groups, matching may be used • Some authorities suggest a quota matrix

16. Pilot Testing, Revising, and Testing

17. Analyzing the Data

18. Validity in Experimentation • Internal validity • Do the conclusions we draw about a demonstrated experimental relationship truly imply cause? • External validity • Does an observed causal relationship generalize across persons, settings, and times?

19. Threats to Internal Validity • History • Maturation • Testing • Instrumentation • Selection • Statistical Regression • Experiment mortality

20. External Validity • The reactivity of testing on X • Interaction of selection and X • Other reactive factors

21. Experimental Research Design • Preexperimental designs • One-shot case study • One-group Pretest-posttest design • Static group comparison • True experimental design • Pretest-posttest control group design • posttest-only control group design • Extensions of true experimental designs • Completely randomized design • Randomized block design • Latin square design • Factorial design