Assignment:
On eCourses is a SPSS dataset called "dataset." This is a made-up dataset examining the influence of a drug on evaluations of male and female faces. The procedure went as follows: all participants evaluated a set of faces on how attractive they found the faces to be prior to receiving the drug. Then they evaluated those same faces after receiving the drug at three time points: 5 minutes after drug administration, 20 minutes after drug administration, and 60 minutes after drug administration. The variables in this dataset are as follows:
id = ID number assigned to participant
pre_female = participants' evaluations of female faces prior to drug administration
pre_male = participants' evaluations of male faces prior to drug administration
post1_female = participants' evaluations of female faces 5 minutes after drug administration
post1_male = participants' evaluations of male faces 5 minutes after drug administration
post2_female = participants' evaluations of female faces 20 minutes after drug administration
post2_male = participants' evaluations of male faces 20 minutes after drug administration
post3_female = participants' evaluations of female faces 60 minutes after drug administration
post3_male = participants' evaluations of male faces 60 minutes after drug administration
Evaluations of attractiveness are measured on a 1-100 scale (1=Extremely Unattractive, 100=Extremely Attractive).
You may use SPSS for all questions. Show all work. That is, please provide SPSS syntax (if not already included in your output) and output. If you do any hand calculations or use Excel, show that work as well.
1.Are you worried about violating HOTDV for the main effect of face gender? the main effect of time? the interaction between face gender and time? Why or why not?
2.Would you use a multivariate approach or univariate approach to analyze your main effect of face gender? your main effect of time? the interaction between face gender and time? Why?
3.Regardless of your answer to #2, report F, p, df, and omega-squared values for all main effects and interaction from the appropriateunivariate analyses. (Note: You should still be taking into account your answer to #1.)
4.Regardless of your answer to #2, report F, p, df, and omega-squared values for all main effects and interaction from themultivariate analysis.
5.Using a multivariate approach, test the following hypotheses. Report F, p, df, and partial eta-squared for each analysis. (NOTE: You do not need to control for Type I error inflation due to multiple comparisons.)
a.The average post-test evaluation (i.e., post1, post2, and post3) of male faces is different from the average post-test evaluation of female faces.
b.There is an effect of time point for male faces.
c.The difference between pre-ratings of attractiveness and post2 ratings of attractiveness is greater for female faces than male faces.