Hi Eric
The longitudinal lme model is no
different from cross-sectional models when it comes to testing the
significance of a covariate. You just simply use an F-test with the
contrast [0 0 0 0 0 1] to test the last covariate in the first model. You can
then drop the last covariate if the test
is
Sorry!
I made a mistake with my example. I meant to say group_effect instead of
rand_effect.
It should read as follows:
Y1 = B1 + B2(time) + B3(group_effect1) + B4(group_effect*time) +
B5(covariate_1) +B6(covariate_2)
Y2 = B1 + B2(time) + B3(group_effect1) + B4(group_effect*time) +
B5(covariate_1
Hello Freesurfer experts,
I have a question about how to determine if a covariate is important in a
mixed effects model
for example:
Y1 = B1 + B2(time) + B3(rand_effect1) + B4(rand_effect*time) +
B5(covariate_1) +B6(covariate_2)
Y2 = B1 + B2(time) + B3(rand_effect1) + B4(rand_effect*time) +
B5(cov
