S********a
发帖数: 359 | 1 下面output最后三行correlation,怎么解释啊，time是fixed effect, id 是random effect, 那么最后的correlation是time 和intercept的correlation?
> #compound symmetry
> fit.gls.cs <- gls(y~time, data=willett, corr=corCompSymm(, form=~time | id
))
> summary(fit.gls.cs)
Generalized least squares fit by REML
Model: y ~ time
Data: willett
AIC BIC logLik
1308.340 1320.049 -650.1698
Correlation Structure: Compound symmetry
Formula: ~time | id
Parameter estimate(s):
Rho
0.7061649
Coefficients:
Value Std.Error t-value p-value
(Intercept) 164.3743 5.774154 28.46725 0
time 26.9600 1.465864 18.39189 0
Correlation:
(Intr)
time -0.381 | a********s
发帖数: 188 | 2 yes, it is the correlation between random intercept and time. | S********a
发帖数: 359 | 3 有什么意义呢？
【在 a********s 的大作中提到】
: yes, it is the correlation between random intercept and time.
| a********s
发帖数: 188 | 4 The negative correlation means large intercept has smaller slope of time, in
your case. | S********a
发帖数: 359 | 5 谢谢，收包子啊
in
【在 a********s 的大作中提到】
: The negative correlation means large intercept has smaller slope of time, in
: your case.
| S******J
发帖数: 30 | 6 I am not familiar with gls but are you sure it is the correlation between
random, not fixed, intercept and time? | a********s
发帖数: 188 | 7 Yes, I am sure about it. | S******J
发帖数: 30 | |
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