Translating R code into Stata code

[Kjell Weyde]

Hi,
I came across a paper by Cole et al (2009; doi: 10.1093/ijc/dyp269) in which they provided R code for a MLE appoach. Does anyone have a suggestion on how to write this in Stata code?

int.p1<-function(xx) {

1/(1+exp(-b0-b1*log(xx)))*dlnorm(xx, c0, c1)

}

int.p0<-function(xx) {

1/(1+exp(b0+b1*log(xx)))*dlnorm(xx, c0, c1)

}

logitln <- function(para){

b0 <<- para[1]

b1 <<- para[2]

c0 <<- para[3]

c1 <<- para[4]

px <- 1/(1+exp(-b0-b1*log(x)))

logL.1<-sum((1-delta)*(y*log(px)+(1-y)*log

(1-px)+log(dlnorm(x,c0,c1))))

logL.2<-sum(delta*y*log(integrate(int.p1,

lower=0,upper=LD)$value)+delta*(1-y)*

log(integrate(int.p0,lower=0,upper=LD)$value))

-(logL.1+logL.2)

}

fit <- optim(par=c(-1, 1, 0, 1), fn=logitln,

hessian = T)

rbind(est=fit$par, se=sqrt(diag(solve

(fit$hessian))))

Kjell Vegard

[Sven-Kristjan Bormann]

See "help mlmethod" or "help mf_moptimize##syn_alleval" for first ideas how to implement likelihood-estimators in Stata or Mata.
The rest should be then rather straightforward. Just translate all the R-commands in Stata-code. I have not tried it myself, but that's at least my naive idea.