F8 发帖数: 348 | 1 dataset with
a binary outcome y/n
4 different studies (treated as an 4-level categorical variable) and 3
treatment for each study
in a logistic model
found significant interaction of trt*study
Now try to consider random effect with study level covariate
As I know that nlmixed can only handle two random effects, in this case
Is there a way to fit a random effect model by treating study as a random
effect? |
c********h 发帖数: 330 | 2 你是说computationally?
try lme4 package in R
glmer(y ~ trt + (trt|study), family = "binomial") |
F8 发帖数: 348 | 3 我的问题是这种情况下用 nlmixed 怎么来 fit random study effect
glmer 相当于sas glimmix ?
能解释一下什么意思吗
哪个是fixed/random effect in this model
study 是categorical 还是 numeric
【在 c********h 的大作中提到】![](/moin_static193/solenoid/img/up.png) : 你是说computationally? : try lme4 package in R : glmer(y ~ trt + (trt|study), family = "binomial")
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d********t 发帖数: 837 | 4 If all you want is study as random effect and treatment as fixed effect ,
that is literally the most straightforward case for glimmix. Not sure what
you are going for .
dataset with a binary outcome y/n4 different studies (treated as an 4-level
categorical ........
【在 F8 的大作中提到】![](/moin_static193/solenoid/img/up.png) : dataset with : a binary outcome y/n : 4 different studies (treated as an 4-level categorical variable) and 3 : treatment for each study : in a logistic model : found significant interaction of trt*study : Now try to consider random effect with study level covariate : As I know that nlmixed can only handle two random effects, in this case : Is there a way to fit a random effect model by treating study as a random : effect?
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F8 发帖数: 348 | 5 I did it actually
the results from glimmix with or without random effects in this case are
identical to the
4-th decimal which is hard to understand
level
【在 d********t 的大作中提到】![](/moin_static193/solenoid/img/up.png) : If all you want is study as random effect and treatment as fixed effect , : that is literally the most straightforward case for glimmix. Not sure what : you are going for . : : dataset with a binary outcome y/n4 different studies (treated as an 4-level : categorical ........
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