Quasi & Non-Experimental Designs

1. Quasi & Non-Experimental Designs Quasi-Experimental designs: Not quite true experiments because the different groups/conditions are not created by random assignment. Groups or conditions are defined by non-manipulated variable or a time variable. Non-Experimental designs – do not allow you to rule out many threats to internal validity.

2. Quasi & Non-Experimental Designs • Those using multiple, nonequivalent groups: • Differential (Causal-comparative) design (non-experimental) • Posttest-only (Static) design (non-experimental) • Pretest-posttest nonequivalent control group design (quasi-experimental) • Cross-sectional design (non-experimental) • Those using one group, compare behavior across time: • Time-series designs (quasi-experimental) • One group pretest-posttest (non-experimental) • Longitudinal design (non-experimental

3. Summary of Quasi & Non-experimental designs

4. Differential (Casual-comparative) Research Definition – Research design in which behavior is measured in 2 groups that differ on 1 primary variable. • The “IV” (not true IV) is the classification or subject variable • Classification variable is not manipulated because it is impossibleorunethical • Normal adults vs. psychopaths • history of abuse vs. no history • Males vs. females • heroine abusers vs. polydrug abusers Does Group A differ from Group B on measures of the DV?

5. Differential (Casual-comparative) Research Intact Group of Participants Intact Group of Participants Measurement of the Dependent Variable Measurement of the Dependent Variable

6. Differential (Casual-comparative) Research Does not demonstrate a causal relationship • There is no guarantee that the two groups will be equivalent in all other ways. • There may be alternative explanations for the observed differences. e.g., kids who play sports vs. those who don’t – compare measures of academic success.

7. Conducting differential (causal-comparative research • Select groups that vary on 1 quantifiable variable • Requires precise definitions • Matching participants – equate groups on extraneous factors • Select extreme groups – more likely to see difference in variable of interest

8. Two groups that differ on some dimension 10 children w/severe behavior problems 10 children w/no behavior problems Compare the two groups Avg. IQ = 103 Avg. IQ = 104 Avg. # hobbies = 4 Avg. # hobbies = 3 Avg. # siblings = 4 Avg. # siblings = 1 History of abuse = 6/10 History of abuse = 3/10 Relationship?

9. Two groups that differ on some dimension 20 smokers 20 nonsmokers Compare the two groups Ed. = High school Ed. = High school Avg. # drinks/day = 2 Avg. # drink/day = 3 15/20 single 5/20 married 3/20 single 17/20 married Relationship?

10. Examples from the media of causal-comparative research: implying causation • Some stress in pregnancy may be good for baby: Children of moderately stressed women are more advanced, study shows • Autism's DNA trail: Gene variant tied to developmental disorder • Music lessons improve kids' brain development, memory: study • Daytime TV tied to poorer mental scores in elderly • Breakfast helps girls stay slim • Eating pizza "cuts cancer risk“ • (having frequent) Sex "cuts public speaking stress"

11. Can you do an experiment? You go downtown at night and measure reaction times of people who have been drinking and those who are sober. Those who have been drinking do worse. • Can you conclude that drinking reduces reaction time? • How could you do this study as an experiment? • Why would we be more confident in the experimental data?

12. Time-Series Design • Definition: A quasi experimental design in which behavior in one group of participants is measured across time before and after an IV is implemented. • Repeated measures control for multiple threats to internal validity • Allows you to evaluate trends across time • Called interrupted time-series when the IV is not created by the experimenter • Called an interrupted time series with switching replications if the IV is presented in two places at different times.

13. Intact Group of Participants Measurement of DV Measurement of DV Measurement of DV Measurement of DV Measurement of DV Experimental Condition Time-Series Design

14. Time-Series Design Example: Effects of anti-smoking campaign on smoking frequency No control group – hard to tell if campaign was effective Time Series – Effect was just part of periodic fluctuation Time Series – Effect was just part of downward trend Time Series – Effect occurs only after intervention

15. Developmental Research Designs – study age-related changes in behavior • Cross-sectional research design • Measure a variable in different age groups • Like a differential group design • Cannot determine how any one individual changes • Other factors may influence groups other than age (cohort/generation effects) Age group 1 e.g., 2-3 Age group 2 e.g., 4-5 Age group 3 e.g., 6-7

16. Group at Time 1 (e.g., 10 yrs) Group at Time 1 (e.g., 20 yrs) Group at Time 1 (e.g., 40 yrs) Developmental Research Designs – study age-related changes in behavior • Longitudinal design • Measuring a variable in individuals over an extended time period • Like a time-series design with no manipulation • Can determine how an individual changes • No cohort effects • Very time consuming, expensive • Problems with attrition, testing

17. Pretest-Posttest Non-Equivalent Control-Group Design

18. Pretest-Posttest Nonequivalent Control-Group Design • Definition: A quasi-experimental design in which behavior in two pre-determined groups is measured pre and post-IV • No random selection and assignment • Because you measure behavior before treatment you can evaluate group equivalence - it reduces the threat of assignment bias • e.g., Effects of Flexible vs. fixed work hours on productivity in two factories • e.g., Effects of Home-based vs. School-based treatment on problem behavior

19. Posttest Only (Static) Group Design

20. Posttest Only (Static) Group Design • No random selection and assignment • 2 naturally assembled groups, e.g., children in 2 clinics • Groups should be similar • Susceptible to internal validity threats, e.g., assignment bias (selection threat) - group assignment is nonrandom • Example: effects of peer tutoring in two classrooms

21. One-Group Pretest-Posttest Design 1 naturally occurring group Pretest and postest

22. One Group Pretest-Posttest Design • Observation made in one group before and after treatment • No attempt is made to control for many threats to internal validity