On May 1, 2013, at 22:40 , Lorenzo Isella wrote:
>
>>
>> (A) The example doesn't run for me. library(ares) is not available on
>> current R versions, but even where it is available, it doesn't provide a
>> multinom() function?
>
>
> Apologies, ares is not needed at all. Please find the correct script at the
> end of the email.
It still doesn't work!!!!!
>
> mymodel <- multinom(ses2 ~ science+ socst+ female, data=mydata)
Error: could not find function "multinom"
>
>
>
Please come up with a _reproduceable_ example. Also show what output you are
getting. And show options("contrasts"); either something has changed them from
the default or we are not talking about the same multinom() function. Halved
coefficients is entirely compatible with using "contr.sum" for unordered
factors.
>
>>
>> (B) If I insert library(nnet), to get a multinom(), I get exactly the same
>> result as Stata does!
>>
>> Did you by any chance diddle with options(contrasts=...)?
>>
>> -pd
>
> No, I did not. The point is that if I use a variable female, which has two
> levels, then I do not reproduce the results of stata for that variable only.
> If instead I define a variable "sex" which assumes the numerical values 0/1,
> then I reproduce entirely the results by stata.
>
> Hope this helps.
>
> Lorenzo
>
>
> ##################################################################
>
>
> library(foreign)
>
> ## See the Stata example at http://bit.ly/11VG4ha
>
> mydata <- read.dta("http://www.ats.ucla.edu/stat/data/hsb2.dta";)
>
>
> sex <- rep(0, dim(mydata)[1])
>
> sel <- which(mydata$female=="male")
>
> sex[sel] <- 1
>
> mydata$sex <- sex
>
> ## IMPORTANT: redefine the base line!!!
>
> mydata$ses2 <- relevel(mydata$ses, ref = "middle")
>
>
> ## NB: for some reason, if I use female (a factor assuming two values)
> ## I do not reproduce the results of the example.
> ## I need to use a variable which is numeric and assumes two values
> ## (that is why I introduced the variable sex))
>
> ## mymodel <- multinom(ses2 ~ science+ socst+ sex, data=mydata)
>
>
> mymodel <- multinom(ses2 ~ science+ socst+ female, data=mydata)
>
>
>
>
> print(summary(mymodel))
>
> print("The relative risk ratio (RRR) is, ")
>
> print(exp(coef(mymodel)))
>
>
>
--
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd....@cbs.dk Priv: pda...@gmail.com
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