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,] 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 > -- View this message in context: http://n4.nabble.com/mlogit-tp1583698p1583698.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
