I'm trying to learn how to use the lrm() function by simulating data using
an old dataset but it's giving me an error I don't understand:
(nst$regular already exists)
nst$regular<-as.ordered(nst$regular)
nst$age<-rnorm(n=942,mean=43.20488,sd=17.03)
nst$age<-round(age,digits=0)
regform<-regular~
I am aware of
table(is.na(df$var))
but is there an efficient way of create a table that shows the number of
missing values in each variable of a data frame?
Right now I am forced to create a new variable, varna<-is.na(df$var), for
each variable of the data frame, bind them to a new data frame an
I entered the following:
formula<-nst~age+soc+inc+reg+imp
pnstlm<-lm(formula,nst)
summary(pnstlm)
imp and soc are ordered categorical variables but the summary does not give
an output of the overall p-values, just individual comparisons. I can't
find help for this in the manual. Is there a co
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