Hi,
I fitted a logistic regression for longitudinal data where the response is a binary variable. I have two variables that are fixed (Sex + Initial_Rythm, both of them are categorical variable) and three variables that changed over time (BIS_0 which is a binary variable, BIS and Lactaat which are two continuous variables).
The model specification is shown here:
proc genmod data= lda;
class ID Initial_Rythm(ref="3") BIS_0 Sex ;
model y(event="1") = Initial_Rythm Sex BIS_0*t BIS*t Lactaat*t t /dist = binomial link = logit;
repeated subject=ID/sorted type=exch;
by _Imputation_;
ods output GEEEmpPEst = lgparms ;
*output out = run_lda p = prob xbeta = logit;
run;
My questions is that: Why do we have even the parameter estimate for the reference group of the interaction term: BIS_0*t. The output of one of the imputed data sets is given below for your reference:
Thank you for any help to clarify this.
I attached in this post the data and the program I used for your convenience.
Hi, I firgured out the solution: I need to add param = ref after the class statement:
class ID Initial_Rythm(ref="3") BIS_0(ref="0") Sex / param = ref ;
So here is the full code:
proc genmod data= lda;
class ID Initial_Rythm(ref="3") BIS_0(ref="0") Sex / param = ref ;
model y(event="1") = Initial_Rythm Sex BIS_0*t BIS*t Lactaat*t t /dist = binomial link = logit;
repeated subject=ID/sorted type=exch;
by _Imputation_;
ods output GEEEmpPEst = lgparms ;
*output out = run_lda p = prob xbeta = logit;
run;
Thank you again, Ksharp. Based on your previous suggestion, I am now able to solve the problem.
Maybe it is using GLM paramterizal method.
Try
proc genmod data= lda;
class ID Initial_Rythm(ref="3") BIS_0(ref="1") Sex ;
OR
proc genmod data= lda;
class ID Initial_Rythm(ref="3") BIS_0(parm=ref) Sex ;
Hi,
Thank you for your reply.
I tried the first option but the output remains the same.
The second option gave an error.
Do you have any other suggestions?
Thank you.
Your data give me is not right , Y has four levels . Check Attachment. proc import datafile='/folders/myfolders/lda_data.txt' out=lda dbms=csv replace; delimiter=' '; run; proc genmod data= lda; where y in (1 12); class ID Initial_Rythm BIS_0 Sex/param=ref ; /* <---------*/ model y(event="1") = Initial_Rythm Sex BIS_0*t BIS*t Lactaat*t t /dist = binomial link = logit; repeated subject=ID/sorted type=exch; ods output GEEEmpPEst = lgparms ; *output out = run_lda p = prob xbeta = logit; run;
Hi Ksharp,
Thank you for giving it a try.
Sorry that when I exported data from a .csv file in R (since this blog does not allow to attacht a .csv file, which I don't know why), it created an additional columns (row.names). That was my fault not to command row.names = F.
So please see here the updated data set which should work correctly.
Thank you.
Hi, I firgured out the solution: I need to add param = ref after the class statement:
class ID Initial_Rythm(ref="3") BIS_0(ref="0") Sex / param = ref ;
So here is the full code:
proc genmod data= lda;
class ID Initial_Rythm(ref="3") BIS_0(ref="0") Sex / param = ref ;
model y(event="1") = Initial_Rythm Sex BIS_0*t BIS*t Lactaat*t t /dist = binomial link = logit;
repeated subject=ID/sorted type=exch;
by _Imputation_;
ods output GEEEmpPEst = lgparms ;
*output out = run_lda p = prob xbeta = logit;
run;
Thank you again, Ksharp. Based on your previous suggestion, I am now able to solve the problem.
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