I am running a model with a grouping variable (Control, Experimental) and Time (0,1,2,3). I want to treat Time as categorical (dummy variables). In addition, I would like to be able to have random slopes. So ... I expect my output to show the variances of the slopes for each dummy variable (e.g., var(0v3), var(1v3), etc.). However, I have been unable to find the correct code/covariance structure that will produce the desired output.
I can get the proper output from R; below we can clearly see the level 1 residual SD, random intercept SD, and the SDs for each dummy variable "slope". Time 3 is treated as the reference category.
m <- lme(dv ~ Time*Group, random = ~ Time|Subj, method="REML", data=d)
summary(m)
Random effects:
Formula: ~Time | Subj
Structure: General positive-definite, Log-Cholesky parametrization
StdDev Corr
(Intercept) 59.79464 (Intr) Time0 Time1
Time0 93.60771 -0.653
Time1 72.42573 -0.277 0.710
Time2 63.31527 -0.462 0.765 0.926
Residual 22.84535
Any help would be greatly appreciated!
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Robert Cribbie
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#SPSSStatistics