l94 - Brief Overview of Manova In this and other handouts,...

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Brief Overview of Manova—Page 1 Brief Overview of Manova In this and other handouts, we’ll briefly go over some advanced techniques that can be useful when estimating complicated models. We won’t discuss these in detail, but at least you’ll know what to look up should you encounter such problems in your research. M ULTIPLE DEPENDENT VARIABLES : M ANOVA . We are often interested in models such as the following: Y1 u X Y2 v Y3 w In this model, there are multiple dependent variables. The IV, X, affects each of them. However, their residuals are also correlated, presumably because of the influence of other variables omitted from the model. The disturbances are connected to each other by two-sided arrows because they are assumed to be correlated, but without a specification of which disturbance is a cause and which is an effect of the others. A common situation in which this occurs is when X is a “treatment” variable, and is coded 0-1 (subject is or is not a member of the treatment group). Why might we want to have more than one dependent variable? In many cases, researchers are not interested in a single measure of group differences. Rather, there are often several components, constructs or behaviors that might be affected by the treatment or that are useful to separate the groups. For example, if we wanted to evaluate the effects of a training program to increase assertiveness, we might be interested in the effects of the program on (1) assertive behavior, (2) anxiety about being assertive, and (3) self-esteem. Another example: Julie Hart’s dissertation looks at the effect of a peer mediation program on
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This note was uploaded on 02/29/2012 for the course SOC 63993 taught by Professor Richardwilliams during the Spring '11 term at Notre Dame.

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l94 - Brief Overview of Manova In this and other handouts,...

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