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Intercept Variance Components Equal 0- Change Score

2 messages · Daniel P Moriarity, Phillip Alday

#
Hello all,

I am revising some MLMs using lmer and a reviewer suggested we use change
scores as our outcome. When I did so, I noticed that the variance
components for the intercept were both 0 (see below) regardless of the
variable I was predicting to (all 6 are now change scores). Any ideas as to
why this might be? The change scores are not person-centered, and we
confirmed that there is between-person variability using the VAR function
(see below the random effects ouput). Thank you.


Random effects:

  Groups   Name        Variance Std.Dev.

ID       (Intercept)  0.00    0.000

Residual             19.46    4.411

Number of obs: 310, groups:  ID, 130
[1] 6.353349


My best,
Daniel

Doctoral Student, Clinical Area
Mood and Cognition Lab
Department of Psychology
Temple University
1701 North 13th Street
Philadelphia, PA 19122
daniel.moriarity at temple.edu <hannah.frank at temple.edu>

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#
Without seeing the rest of your model, it's hard to tell. I suspect you
model is something like:

change_score ~ 1 + some_predictor + (1|ID)

Then you only have a few change_scores by participant and the
by-participant variation is indistinguishable from the residual
variation. Because the random-effect for participant measures the
variation due to participant *beyond* the residual variation, it goes to
zero here.

Phillip
On 14/09/2019 05:03, Daniel P Moriarity wrote: