I have repeated (x4) measurements on 90 subjects. The outcome is zero inflated.
The model output gives these estimates:
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -2.2151 1.6998 -1.30 0.193
time 0.5283 0.2167 2.44 0.015
X 0.0791 0.3267 0.24 0.811
time:X -0.1525 0.0611 -2.49 0.013
Y 1.0348 0.4488 2.31 0.021
time:Y -0.0037 0.0583 -0.06 0.950
Number of observations: total=342, Subject=90
Random effect variance(s):
Group=Subject
Variance StdDev
(Intercept) 6.302 2.51
Negative binomial dispersion parameter: 3.9265 (std. err.: 0.69723)
Zero-inflation: 0.13169 (std. err.: 0.027756 )
X and Y both vary at the subject-level only, not at the time-level.
As you see, here the main effect of X is not significant, while the time:X interaction is significant. On the other hand, the main effect of Y is significant, while the time:Y interaction is not.
I believe that in the case of Y, this means that subjects with higher values of Y have higher trajectories of the outcome. Is this correct ?
However, how is the time:X interaction to be interpreted ?
