[R] Loop through variables and estimate effects on several outcomes

[arun]

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) 
>})