[R] Loop through columns of outcomes

[Rui Barradas]

Hello,

Use nested lapply(). Like this:



m1 <- lapply(varlist0,function(v) {
	lapply(outcomes, function(o){
		f <- sprintf("%s~ s(time,bs='cr',k=200)+s(temp,bs='cr') + 
Lag(%s,0:6)", o, v)
		gam(as.formula(f),family=quasipoisson,na.action=na.omit,data=df)
       })})

m1 <- unlist(m1, recursive = FALSE)
m1


Hope this helps,

Rui Barradas


Em 12-11-2013 09:53, Kuma Raj escreveu:
> I have asked this question on SO, but it attracted no response, thus I am
> cross- posting it here with the hope that someone would help.
>
> I want to estimate the effect of  pm10 and o3 on three outcome(death, cvd
> and resp). What I want to do is run one model for each of the main
> predictors  (pm10 and o3) and each outcome(death, cvd and resp). Thus I
> expect to obtain 6 models. The script below works for one outcome (death)
> and I wish to use it for more dependent variables.
>
>
>
> library(quantmod)
> library(mgcv)
> library(dlnm)
> df <- chicagoNMMAPS
> outcomes<- c("death", "cvd", "resp ")
> varlist0 <- c("pm10", "o3")
>
>      m1 <- lapply(varlist0,function(v) {
>          f <- sprintf("death~ s(time,bs='cr',k=200)+s(temp,bs='cr') +
> Lag(%s,0:6)",v)
>          gam(as.formula(f),family=quasipoisson,na.action=na.omit,data=df)
>        })
>
> Thanks
>
> 	[[alternative HTML version deleted]]
>
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