Message/Author
 Seth J. Schwartz posted on Monday, March 28, 2011 - 11:41 am
Dear Bengt and Linda:

I am running two models: one ANOVA-like model where I use dummy-coded variables for three of the four categories used, and the other an ANCOVA-like model where I add a continuous covariate in addition to these dummy-coded predictors. I am getting means for the various groups by adding the coefficient for a given group to the intercept term. This works well for the model without the covariate, but in the model with the covariate I am getting adjusted means that are outside the range of possible scores for the dependent variable. Am I doing something wrong, or is this what should be happening?

Again, thank you very much.

Seth Schwartz
 Bengt O. Muthen posted on Monday, March 28, 2011 - 4:53 pm
The covariate mean may be different in the different groups. The beta*mean term for this covariate needs to be included when you compute the estimated means.
 Nadine Forget-Dubois posted on Friday, September 09, 2011 - 9:19 am
Dear Bengt and Linda:

I am also trying to compute adjusted means for the DV in an ANCOVA-like model.

Model:

heightav on group1;
heightav on group2;
heightav on group3;
heightav on test_age;

I don't understand what you mean by including the beta*mean term for this covariate, can you give an exemple?

Thanks!

 Bengt O. Muthen posted on Saturday, September 10, 2011 - 8:44 am
Using your example, I assume you have 4 groups and the 3 group variables that you mention are 0/1 dummy scored where only one of them has a value 1 while the others are 0, and when all 3 are zero this refers to the 4th group. I also assume that test_age is continuous. Then what I meant was that the mean of heightav for group j (j=1 or 2 or 3) is

intercept+betaj+beta*test_age,

where betaj is the slope for heightav ON groupj and beta is the slope for heightav ON test_age.

The mean of heightav for the 4th group is

intercept+beta*test_age.