Unit 5: Repeated Measures ANOVA

The assignment this week is to complete a repeated-measures ANOVA. The data for this assignment can be found on page 368 of the Howell text, Exercise 18.1, in the CD (EX18-1.sav) and in the unit 5 datafile . Howell adapted data originally collected by Nolen-Hoeksema and Morrow (1991) from research directed at measuring depressive symptoms of selected college age students in California who had experienced the Loma Prieta earthquake. It will be assumed that higher scores on the measure of depression indicate greater depression. The students were assessed on five occasions, starting two weeks prior to the earthquake and continuing every three weeks until five repeated measures had been collected.

SPSS Hints

After the data file is entered or loaded in SPSS, there should be 25 cases and five variables (columns). If you kept the variable names (a good idea), the variables will be labeled week0, week3, etc.

For initial review of the variables and data distributions, produce a Pearson correlation matrix using all five weeks as the variables (analyze, correlate, bivariate). One of the requirements of repeated-measures ANOVA (beyond the assumptions associated with between-subjects ANOVA) is that the correlations among the levels of each factor should be relatively consistent. Stated another way, the correlations among all weeks should be about the same. Examine the correlation table to see if this seems a reasonable assumption for this data. SPSS also provides a test of this assumption called the Mauchly test of sphericity. If this statistic is not significant at the normal alpha levels, then the assumption is tenable.

•  In addition, run Explore (under Analyze / Descriptives ) and enter all five variables in the window for the dependent list.

•  Request outliers in the Statistics option and in the Plots option, check the box for Displays Box Plots Together (dependents together).

•  To run the repeated-measures analysis, go to Analyze / General Linear Model / Repeated Measures .

•  This design is a single factor (weeks) with five levels (each week), so enter that information in the appropriate boxes and then click Add and then Define .

•  In the next window that appears, select all five weeks and move each week over into the Within Subject Variables box. You have told SPSS that this is a one-factor repeated measures design with five levels.

•  At the bottom of that window, click Options , and move weeks into the Display Means For box.

•  Check the Compare Main Effects box and check Display Descriptives , Effect Size , and Power . Then continue and run the analysis (Click OK ).

When the output is produced, examine the table labeled "Within-Subjects Effects" and, if sphericity can be assumed, use the appropriate row for identifying the needed F. You should be able to interpret all the columns, except possibly the one labeled "noncent. Parameter," which is unimportant anyway. Next, proceed to the table of "Tests Of Within-Subject Contrasts." What is being tested here is if there are trends (or a pattern of increase or decrease) across the levels (weeks). This could be a linear pattern, consistently increasing or decreasing, or a curvilinear pattern that goes up and down and has peaks and valleys. Find the table that shows the means for each week (i.e., estimated marginal means). Do you see a trend in the means across weeks? Maybe there is more than one type of trend. Return to the table of "Tests Of Within-Subject Contrasts" and interpret the results for the presence of a trend or trends. Finally, go to the table of "Pairwise Comparisons" and interpret which weeks are statistically different from which other weeks. Summarize what you have found in relation to the original research problem (adjustment to the earthquake). What would be reasonable conclusions for this study? What are the limitations of this study?

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