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Lecture 10


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York University
PSYC 2230
N/ A

RESEARCH METHODS LECTURE 10: TUESDAY JULY 31ST, 2012 TOPIC: QUASI-EXPERIMENTAL DESIGNSAND APPLIED RESEARCH You cannot randomly assign people to groups QUASI EXPERIMENTAL DESIGNS ➔ Procedures resemble those of true experiments ➔ But lack the degree of control found in true experiments ➔ Generally occur when the IV involves: subject variables (e.g personality type), an environmental event (e.g. hurricanes or having a particular classroom teacher), the passage of time ➔ Hedrick, Bickman and Rog (1993) “a quasi-experimental design is not the method of choice, but rather a fallback strategy” ➔ Cannot infer cause and effect, BUT well designed quasi-experiments enable you to demonstrate that rival interpretations are rendered unlikely ➔ These designs are correlational NON EQUIVALENT GROUP DESIGNS ➔ Post test only nonequivalent control group design (aka static group comparison) ➔ X O (treatment group) ➔ O (nonequivalent control group) ➔ x=treatment ➔ o=measurement/observation ➔ Because there is no random assignment to groups, confounding variables may explain any difference observed. ➔ No randomly assigned → therefore we do not know if the two groups are equivalent at the beginning ➔ Most common threat to internal validity of this type of design is SELECTION ➔ This is because the two groups may be different on a number of variables such as age gender IQ but we do not know. It is unlikely for matching to work because we cannot match on every variable ➔ Example: IV Training Program and No Training Program DV Smoking measure and smoking measure. Two groups of participants. No control of who is in each group. Experimental group = people who volunteer for the program and control group could be who did not sign up ➔ Selection problem = smokers who choose to participate may differ in some important way from those who do not. Maybe the ones who wanted to do this will be more motivated and those who did not will not be. This will make it seem as though the treatment is successfully when it could be due to other factors ➔ Pre-test/ Post-test non-equivalent control group ➔ O X O treatment group and non-equivalent control group ➔ O O ➔ Pre Post ➔ Addition of the pretest measurement allows the researcher to compare the observations before treatment ➔ Design also allows a researcher to compare the pre test scores and post test scores for both groups ➔ It is important to know that you may not be able to compare every variable and aspect between both groups ➔ Example: Research methods and ReasoningAbility ➔ Intervention: critical thinking seminar ➔ Research Methods students receive the intervention (i.e. participate in the critical seminar) ➔ Developmental Psychology students are used as a nonequivalent control group (i.e. do not attend the seminar) ➔ Graph is shown ➔ Both groups increased but the slope of the line of the developmental group is steeper therefore critical thinking scores would go up regardless in comparison to thinking participating in the program would increase your scores greatly ➔ What threats to internal validity cannot be ruled out? ➔ May have different experiences (selection-history effect) ➔ May mature at different rates (selection-maturation effect) ➔ Be measured more or less sensitively by the instruments (selection-instrumentation effect) ➔ May drop out of the study at different rates (differential subject mortality) ➔ May differ in terms of regression to the mean (differential regression) ➔ How severe are these problems? Heinsman and Shadish (1996) True experiments versus quasi experiments ➔ Quasi-experiments very similar to those of true experiments ➔ When the quasi-experiments were characterized by: small differences between the group and control on the pre-tests, low attrition rates, low levels of participant self-selection into conditions INTERRUPTED TIMES SERIES DESIGNS ➔ Extension of the simple one group pre post design ➔ Participants are pre-tested a number of times and then post-tested a number of times after being exposed to the treatment intervention ➔ O1 O2 O3 O4 X O5 O6 O7 O8 → observations before and after treatment O: observation X: treatment ➔ Useful when one cannot randomize participants, it is possible to obtain a series of assessments of the DV before and after treatment ➔ Goal: evaluate the influence of the treatment by comparing the observations made before treatment with the observations made after ➔ Example: Intervention: course to change students' study habits, implemented during the summer (after semester 4)
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