Types of Research and Designs

1. Types of Research and Designs • This week and next week… • Covering • Research classifications • Variables • Steps in Experimental Research • Validity • Research Designs • Common Sources of Error

2. RESEARCH DESIGNS

3. Types of Designs • Research designs are ways to structure and conduct research in order to avoid the threats to internal and external validity. • Pre-experimental designs • True experimental designs • Quasi-experimental designs

4. Pre-experimental Designs • Fewest controls • No random sampling • No random assignments • Controls few threats to validity

5. True Experimental Designs • Most controls • Random sampling • Random assignments • All threats to internal validity controlled

6. Quasi-experimental Designs • Some controls • (maybe) random sampling • (maybe) random assignments • Not all threats to internal validity controlled, but attempts are made to control some of them.

8. Types of Designs • Research designs are ways to structure and conduct research in order to avoid the threats to internal and external validity. • Pre-experimental designs • True experimental designs • Quasi-experimental designs

9. Design Complexity • X = treatment administered • O = data collected • Example: • O1 – X – O2 • Pre-test vs. post-test design • Look at Table 7.2…

11. Methods of Control • Physical manipulation • Researcher controls all aspects • Selective manipulation • Selecting certain participants controls threats to internal and external validity • Matched pairs and block designs • Participants with similar scores on a dependent variable are matched into pairs (for two groups) or into blocks if more than two groups are needed. • The participants are still randomly assigned to the treatment groups • This procedure allows comparisons between or among groups that started equally

12. Methods of Control • Counterbalanced design • All participants receive all treatments, but in random order • Example: • Sarah?

13. Methods of Control • Statistical techniques • When physical and selective manipulations of variables cannot be accomplished • Groups differ on a known variable, but you can’t do anything about it in terms of the design • There are many ways to statistically control for these differences • ANCOVA (analysis of covariance) • Adjusts the differences among groups (variates) based on the common variability in one variable (the covariate) • Normalization • A technique that is commonly used to reduce between-subject and between-group variability • Limited to looking at the “patterns” in the data

14. COMMON SOURCES OF ERROR

15. Common Sources of Error • Hawthorne Effect • Placebo Effect • “John Henry” Effect • Rating Effect • Experimenter Bias Effect • Participant-Researcher Interaction Effect • Post Hoc Error

16. Hawthorne Effect • Named after a study conducted at the Hawthorne Electric Plant in the 1920’s. • It was observed that a group of workers that participated in the study acted differently because they “felt special.” • Therefore, participants should… • Be unaware that they are participating in a study • Be unaware of the hypotheses being tested • Within the confines of human subject research restrictions

17. Placebo Effect • If participants believe that a change is supposed to occur as a result of a treatment, they will respond with a change in performance (no matter what the treatment is). • Therefore, participants should… • Be randomly assigned to treatment and placebo groups

18. “John Henry” Effect • Participants know that they are in a control group and that the experimental group is supposed to be better, therefore, the control group tries harder to outperform the experimental group. • Therefore, participants should… • Not be aware of the group they are in • If they all think they are in a control group, they will all try hard.

19. Rating Effect • Several kinds of rating effects: • Halo effect: • The tendency to let initial impressions or ratings of a participant or group influence future ratings. • Over-rater/under-rater error • When researchers tend to over- or under-rate subjects • Central tendency error • When researchers rate subjects toward the middle of the scale • When subjects rate issues toward the middle of the scale

20. Experimental Bias Effect • The bias of a researcher can effect the outcome of a study. • Therefore, studies should be blinded. • Single blinded studies • Only the subjects are blinded to the treatments • Double blinded studies • Subjects and investigators blinded to the treatments

21. Participant-Researcher Interaction Effect • How participants respond to different researchers. • Sometimes, males and females respond differently to male vs. female researchers. • Therefore, researchers should… • Act and respond to subjects exactly the same way each time (professionally)

22. Post Hoc Error • Error that is introduced by assuming a cause-and-effect relationship between two variables • Example: • More people die in a bed than any other place; therefore, beds are dangerous. • Therefore, researchers should… • Not assume cause-and-effect relationships without sufficient evidence