(To be done by computer.) The chapter talks at some length about the best way to analyze data from a randomized pretest-posttest design. To see how various analytic strategies might compare to one another in a realistic situation, let’s return to the data shown in Table 9.7. Recall that Table 9.9 presented ANCOVA results for these data. a. Because groups were randomly assigned here, it might seem acceptable to ignore pretest scores in comparing the groups on the posttest. Test to see whether there is a significant difference between groups on the pretest. b. Based on your answer to part a, you might decide to proceed to conduct an ANOVA on posttest scores, ignoring pretest scores. How do your results compare to the ANCOVA results In particular, does the ANOVA yield a statistically significant result at the .05 level? c. Another possible approach might be to analyze gain scores. Conduct an ANOVA on gain scores. How do your results compare to the ANCOVA results In particular, does the ANOVA yield a statistically significant result at the .05 level? d. A colleague suggests that your pattern of results implies that ANCOVA appeared superior because it exaggerated the differences between the groups. How would you respond to this colleague’s statement? e. What do your results comparing the three different approaches suggest about the relative merits of ANCOVA, ANOVA on posttest only, and ANOVA on gain scores for analyzing data from randomized pretest-posttest designs?
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