On Mar 7, 2010, at 12:06 PM, cmc wrote:
I am trying to follow this example for multinomial logistic regression
http://www.ats.ucla.edu/stat/r/dae/mlogit.htm
However, I cannot get it to work properly.
This is the output I get, and I get an error when I try to use the
mlogit
function. Any ideas as to why this happens?
mydata <- read.csv(url("http://www.ats.ucla.edu/stat/r/dae/
mlogit.csv"))
attach(mydata)
names(mydata)
[1] "brand" "female" "age"
library(mlogit)
Loading required package: Formula
Loading required package: statmod
mydata[1:10,]
brand female age
1 1 0 24
2 1 0 26
3 1 0 26
4 1 1 27
5 1 1 27
6 3 1 27
7 1 0 27
8 1 0 27
9 1 1 27
10 1 0 27
mydata$brand<-as.factor(mydata$brand)
mldata<-mlogit.data(mydata, varying=NULL, choice="brand",
shape="wide")
mldata[1:10,]
You do not get the same result as the example page, (while I do). You
need to see if you have other objects with names that may be confusing
the interpreter. I did not attach() mydata, which despite the UCLA's
use of it is considered bad practice in R programming because of
frequent obscure bugs that trip up newbies such as us. The errors do
not occur when the next commands are run.
brand female age
1.1 TRUE 0 24
1.2 FALSE 0 24
1.3 FALSE 0 24
2.1 TRUE 0 26
2.2 FALSE 0 26
2.3 FALSE 0 26
3.1 TRUE 0 26
3.2 FALSE 0 26
3.3 FALSE 0 26
4.1 TRUE 1 27
mlogit.model<- mlogit(brand~1|female+age, data = mldata,
reflevel="1")
Error in as.data.frame.default(data) :
cannot coerce class "call" into a data.frame
summary(mlogit.model)
Error in summary(mlogit.model) : object 'mlogit.model' not found
--
David Winsemius, MD
West Hartford, CT
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