Hi,
I am having difficulty understanding some lme output -- I haven't found too
many examples to help explain to me how to interpret the coefficients and would
appreciate any help.
I am fitting a model:
fit <- lme(y ~ pre + group + time + group:time, random=~1|subject,
na.action=na.omit, data=mydata)
...for a dataset where there are two groups being followed over time. pre is
before the treatment, and there are 4 post-treatment times (unequally spaced).
The fitted coefficients are:
(Intercept) pre group2 time2 time3 time4 group2:time2 group2:time3
group2:time4
2.6442 0.5478 1.0183 0.6085 0.2326 0.5059 -1.9177 -0.3500
-2.2029
of which there are only significant p-values (<0.05) for (Intercept), pre,
group2:time2 and group2:time4.
anova(fit) gives:
numDF denDF F-value p-value
(Intercept) 1 864 550.9939 <.0001
pre 1 348 129.1674 <.0001
group 1 348 0.0049 0.9444
time 3 864 0.6715 0.5697
group:time 3 864 2.7206 0.0434
What I can't seem to do is understand how to correctly interpret the
coefficients about what is going on. I have been trying to work out the
coefficients by subtracting various means but am getting nowhere.
Is anyone able to give me kind hand?
Rachel
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