Dear R List,
I am trying to use mixed models to analyze an intervention and want to make
sure I am doing it correctly. The intervention is for lowing cholesterol
and there are two groups: one with an intervention and one without. The
subjects were evaluated a differing amount of time, so there were between 2
and 7 visits, equally spaced.
Sample output is below. TC is total cholesterol, group.minus.1 is the
intervention indicator and Study.Number is the subject id. If I'm reading
this correctly, the t-value on group.minus.1 is 0.63 and so the intervention
did not have a significant effect. Is that the correct way of interpreting
this?
Troy
Linear mixed model fit by REML
Formula: TC ~ group.minus.1 + Visit + (Visit | Study.Number) + (1 |
Study.Number)
Data: rawdf
AIC BIC logLik deviance REMLdev
4676 4710 -2330 4670 4660
Random effects:
Groups Name Variance Std.Dev. Corr
Study.Number (Intercept) 857.440 29.2821
Visit 21.471 4.6337 -0.755
Study.Number (Intercept) 508.757 22.5556
Residual 333.710 18.2677
Number of obs: 494, groups: Study.Number, 140
Fixed effects:
Estimate Std. Error t value
(Intercept) 162.3291 4.4392 36.57
group.minus.1 3.4466 5.4699 0.63
Visit -1.4515 0.5997 -2.42
Correlation of Fixed Effects:
(Intr) grp..1
group.mns.1 -0.593
Visit -0.493 -0.043
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