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I have two vectors (A and B) with categorical data of 36 subjects. A_i,j being the categorytype1 j, subject i fits into and B_i,k is categorytype2 k of subject i. With i=1:36, j=1:5 and k=1:6.

library(mlogit)
AB <- read.csv("C:/.../AB.csv")
head(AB)
   Subject     A     B 
 1       1     1     3 
 2       2     3     3 
 3       3     1     6 
 4       4     1     3 
 5       5     1     2 
 6       6     1     4

I would like to find a probability for every category combination. So with what chance does a subject choose category j and k for all j=1:5 and k=1:6.

I was told the probit/logit model was a great tool to use for this problem and I tried estimating it in R. 

mldata<-mlogit.data(AB, choice="A", alt.var="B", shape="long", id.var = "Subject")

Gives me an error and I can not find my mistake. 

Error in `row.names<-.data.frame`(`*tmp*`, value = c("1.3", "1.3", "1.6",  : 
duplicate 'row.names' are not allowed
In addition: Warning message:
non-unique values when setting 'row.names': ‘1.3’, ‘2.2’, ‘2.3’, ‘3.1’,‘3.5’,‘4.2’,‘4.3’, ‘5.3’, ‘5.4’, ‘6.5’, ‘7.3’, ‘8.2’, ‘8.3’

I tried looking through the help files but has not helped me a lot.

I hope someone can point out the mistake(s) I'm making.

Thank you very much for your help.

user3681343
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1 Answers1

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Post output of dput(A) and dput(b) and specify what the first couple of answers should be. . Looks like you want rowSums(.)/6 across some logical operation on those two matrices. Probably:

 rowSums(A==B)/6
IRTFM
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