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.
How to model multiple categorical variable in r, using gee model
2 messages · augustinus ntjamba, Jim Lemon
Hi Augustinius, You have been set a problem that requires a lot more information than is in your request. Also, you have flagged it as a "homework" problem, so you are unlikely to get much help on this list. Sadly, this sort of problem sometimes arises when being nice to the instructor is more important than having the relevant knowledge and I can't help you with that. Jim On Mon, Sep 21, 2020 at 10:39 PM augustinus ntjamba
<augustinusyantjamba at gmail.com> wrote:
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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