[R] How to model multiple categorical variable in r, using gee model

augustinus ntjamba @ugu@t|nu@y@ntj@mb@ @end|ng |rom gm@||@com
Mon Sep 21 02:47:10 CEST 2020


Good morning.
I'm a student at present working on my final year project.
Kindly asking for help on how to model longitudinal categorical data.

In my data set I have the following variables :type of crime,year,   month,
date and time.treating type of crime as the response variable and there's
12 levels  (Type of crime), while the rest of the variables are
independent.
What model will best fit my data?

I have tried using geeglm And this does show differences in correlation
matrix that should be selected as the best model, secondly I tried using
multgee package "multLORgee" which never have me outputs and lastly I tried
using multnom the function returns the same AIC in the working correction
matrix,
How do i solve this problem
Thank you.

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