Dear all,
I am thinking to fit a multilevel dataset with R. I have found several
possible packages for my task, such as
glmmPQL(MASS),glmm(repeated),glmer(lme4), et al. I am a little confused by
these functions.
Could anybody tell me which function/package is the correct one to analyse
my dataset?
My dataset is as follows:
the response variable P is binary variable (the subject is a patient or
not);
two explanatory variables X1 (age) and X2 (sex);
this dataset was sampled from three different level,
district,school,individual, so this was regarded as a multilevel dataset.
I hope to fit the 3-level model(Y is binary variable):
Logit(Pijk)=(a0+b0k+c0jk)+b1*X1+b2*X2
i-individual, first level; j-school, 2nd level; k-district,3rd level.
I know that the GLIMMIX procedure in the latest version SAS9.2 is a choice
for that, but unfortunately we donot have the latest version.
R must have the similar functions to do that, can anybody give me some
suggestions or help on analysing my dataset?
Q1: Which package/functions is appropriate for my task? Could u show me
some example codes if possible?
Q2: Logit(Pijk)=(a0+b0k+c0jk)+(b1+b1j)*X1+b2*X2
If the randome effect was also specified in X1 as above, Which
package/functions is possible?
Thanks a lot.
--
With Kind Regards,
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ZhiJie Zhang ,PhD
Dept.of Epidemiology, School of Public Health,Fudan University
Office:Room 443, Building 8
Office Tel./Fax.:+86-21-54237410
Address:No. 138 Yi Xue Yuan Road,Shanghai,China
Postcode:200032
Email:[EMAIL PROTECTED] <[EMAIL PROTECTED]>
Website: www.statABC.com
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