I need to determine whether a variable y2e increases with a covariate xt within
individuals, where individuals a-j are measured several times.
Is it possible to test whether within-group coefficients are significantly
different from zero?
The coefficients from an lmList fitted to my data give:
> coef(lml2)
(Intercept) xt
a 3.5689877 -0.05413678
b -0.1432629 0.02558787
c 6.9933976 -0.04593475
d -1.2205123 0.03419385
e 11.4861355 -0.02997357
f -13.1410819 0.06999514
g 25.1284971 -0.05560643
h 26.9868990 -0.04947859
i 23.1811000 -0.03006984
j -18.3750713 0.05958911
doing summary(lme(lml2)) appears to give the coeffient across groups, which is
not of interest:
> summary(lme(lml2))
...
Fixed effects: y2e ~ xt
Value Std.Error DF t-value p-value
(Intercept) 0.28520893 0.7168887 489 0.397843 0.6909
xt 0.02133808 0.0023420 489 9.110898 0.0000
...
Many thanks,
Dan Bebber
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