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)

The difference between the two that I was trying to highlight is the presence of the second covariate term.

Thanks,

-E

On Tue, Mar 4, 2014 at 11:18 AM, Eric Cunningham <etc42@hawaii.edu> wrote:

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(covariate_1)

Would it be appropriate to use the lme_mass_LR script?  (the script says it is for comparing models with q and q+1 random effects). 

Thanks,

-E

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