Hi,
Try:
hsb2 <- read.csv("http://www.ats.ucla.edu/stat/data/hsb2.csv";)
varlist<-names(hsb2)[8:10]
fun2<- function(varName){
res<- sapply(varName,function(x){
model1<-
lm(substitute(cbind(female,race,ses)~i,list(i=as.name(x))),data=hsb2)
sM<- summary(model1)
sapply(sM,function(x) x$coef[2,1])
})
res
}
fun2(varlist)
# write math science
#Response female 0.01350896 -0.001563341 -0.006441112
#Response race 0.02412624 0.022474213 0.033622966
#Response ses 0.01585530 0.021064315 0.020692042
A.K.
>This post has NOT been accepted by the mailing list yet.
>I want to estimate the effects of an exposure on several outcomes. The example
>in this link provides how to loop though variables which are
>explanatory variables.
>http://www.ats.ucla.edu/stat/r/pages/looping_strings.htm
>The
example below estimates the effects of several variables on read. But I
want to estimate the effect of "female" , "race" , "ses" on
"write" , >"math" "science" one at a time using the hsb data set.
How can I loop through these outcomes?
>varlist <- names(hsb2)[8:11]
>models <- lapply(varlist, function(x) {
> lm(substitute(read ~ i, list(i = as.name(x))), data = hsb2)
>})
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