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 )
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 ?