Posted by
Jeff-125 on
Aug 07, 2006; 3:44pm
URL: http://spssx-discussion.165.s1.nabble.com/Multiple-Regression-Interactions-tp1070140p1070142.html
At 06:01 AM 8/7/2006, you wrote:
>Does anyone know whether there are sample size requirements for dichotomous
>predictors in multiple regression? That is, for the dichotomous predictor,
>what is the smallest number of cases per group that is allowed?
>
>Also, I have another query regarding interpreting interaction effects in
>SPSS's multiple regression. When a cross product term is created by
>multiplying together a predictor which is positively associated with the DV
>(e.g., happiness) and a predictor that is negatively associated with the DV
>(e.g., depression), would the resulting product term be expected to show a
>positive or negative beta coefficient? I'm sure there's a really simple
>answer to this.
>
>Thank you in advance.
>K S Scot
Regarding the first issue - I'm not sure I understand - mathematically, the
number of cases doesn't matter as long as it isn't a constant - e.g., all
cases are in the same group. Practically, if you have a small number of
cases in one group, you won't be able to accurately examine the group
differences - i.e., you may get an estimate for the regression coefficient,
but the p value will be high.
Regarding the second issue - the sign of the bivariate correlations doesn't
really matter. What matters is whether there is an interaction between the
effects (by definition). In other words, let's say Happy-days/month is
positively related to amount of time spent outside of house/month, while
depression/month is negatively related. A significant interaction, for
example, might imply that if there are many depressed days/month, the
desire to go outside during happy days is reduced.
Jeff