Chapter 12 Experimental Designs

2. Chapter 12 Experimental Designs

3. Chapter Objectives • understand the role and scope of experimental research in business • distinguish between causal and correlational analysis • explain the difference between laboratory and field experiments • explain the following terms: extraneous variables, manipulation, experimental and control groups, treatment effect, matching and randomisation • discuss the seven possible threats to internal validity in experimental designs • describe the different types of experimental designs • explain the role of simulation in experimental research • describe the ethical issues involved in experimental research

4. Experimental Designs Laboratory Experiment Field Experiment Cause: - Effect relationships established by: 1. Manipulating treatments 2. Controlling for external or exogenous variables Manipulation of Treatment: Example: Three different teaching methods given to three different groups of students Straight lectures to 10 students simulation only, to another 10 students Both lectures and simulations to 10 other students Assess which results in greatest amount of learning

5. Simulation alone is ineffective. • Lectures are more effective than no treatment at all. • Both lectures and simulation are extremely effective. • Cause: - Effect relationship can be established because of: • Controls for age, etc. through either randomisation or matching of groups • Because of an additional control group

6. Control of Exogenous Variables through; • Random assignment of members to various groups • Matched groups • Control groups • Example: Different treatments may have different effects on people with differing interests, ages, expertise,etc. • So, a) randomly assign members to different treatment groups. The differences will be randomly distributed. Systematic bias will be reduced. • b) match the different groups as closely as possible in terms of age, interest, expertise, etc. • c) have an additional control group of students who ar not exposed to any of the three treatments, and see how they learn and compare.

7. Controlled Variables Variables that might affect the Cause - Effect relationship among the IVs and DV, and hence need to be controlled. Example: 1. Age 2. Education levels 3. Length of Service in Organisation Might affect the relationship between job characteristics and job satisfaction

8. Uncontrolled Variables Variables or phenomena that occur unexpectedly and can confound the results. Example: Advertising Purchasing (IV) (DV) • Age • Life style Sudden Unemployment (Uncontrolled Variable) (Controlled Variables)

9. Lab Experiements can have tight controls and hence the validity of cause – Effect findings is high – ie., they have high internal validity. But their generalisability to real life is low, because of their tight controls – ie., their external validity is low. Field Experiments (eg, different incentive plans (treatment0 in work organisations for assessing effect on productivity, have high external validity or generalisability (because they represent the actual situations), but have low internal validity (ie., cause – effect relationships are contaminated because of no controls.)

10. Cause and effect relationship after randomisation

11. FACTORS AFFECTING INTERNAL VALIDITY • HISTORY EFFECTS • MATURATION EFFECTS • TESTING EFFECTS • INSTRUMENTATION EFFECTS • SELECTION BIAS • STATISTICAL REGRESSION • MORTALITY

12. History effects inexperimental design

13. Maturation effects on the cause and effect relationship

14. Pre-test and post-test experimental group design

15. Post-test only with experimental and control groups Treatment effect = (O1 - O2)

16. Pre-test and post-test experimental and control groups Treatment effect = [(O2 - O1) – (O4 -O3)]

17. Solomon four-group design Treatment effect (E) could be judged by: E 1 = (O2 - O1) E 2 = (O2 - O4 ) E 3 = (O5 - O6) E 4 = (O5 - O3 ) E 5 = (O2 - O1) – (O4 - O3 ) If all Es are similar, the cause and effect relationship is highly valid.

18. Major threats to internal validity in different experimental designs

19. Simulation as experimentation

20. Example of a managementflight simulator

21. Ethical Issues in Experimental Research The following practices are considered unethical: • pressuring individuals to participate in experiments through coercion or applying social pressure • giving out menial tasks and asking demeaning questions that diminish the subject’s self-respect • deceiving subjects by deliberately misleading them as to the true purpose of the research • exposing participants to physical or mental stress • not allowing subjects to withdraw from the research when they want to

22. Ethical Issues in Experimental Research(cont’d) • using the research results to disadvantage the participants, or for purposes that they would not like • not explaining the procedures to be followed in the experiment • exposing respondents to hazardous and unsafe environments • not debriefing participants fully and accurately after the experiment is over • not preserving the confidentiality of the information given by the participants • withholding benefits from control groups

23. Decision points for embarking on an experimental design

24. A completely randomised design

25. A randomised block design Blocking factor: residential areas Note that the Xs above indicate only various levels of the blocking factor, and the Os (the number of passengers before and after each treatment at each level) are not shown, although these measures will be taken.

26. The Latin square design Day of the week

27. A 3 * 3 factorial design