[R] what's wrong with my simulation programs on logistic regression

[Dimitris Rizopoulos]

In this way you don't simulate response data; it'd also be a good idea 
to consider a bigger sample, e.g.,

dat <- matrix(rnorm(4000), ncol = 8)
dat <- data.frame(dat)
names(dat) <- paste("x", 1:8, sep = "")
dat$y <- rbinom(nrow(dat), 1, plogis(rowSums(dat)))

fit <- glm(y ~ ., family = binomial, data = dat)
fit

I hope it helps.

Best,
Dimitris

----
Dimitris Rizopoulos
Ph.D. Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven

Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/(0)16/336899
Fax: +32/(0)16/337015
Web: http://med.kuleuven.be/biostat/
     http://www.student.kuleuven.be/~m0390867/dimitris.htm


----- Original Message ----- 
From: "zhijie zhang" <epistat at gmail.com>
To: <R-help at stat.math.ethz.ch>
Sent: Thursday, August 31, 2006 4:12 PM
Subject: [R] what's wrong with my simulation programs on logistic 
regression


> Dear friends,
> I'm doing a simulation on logistic regression model, but the 
> programs can't
> work well,please help me to correct it and give some suggestions.
> My programs:
> data<-matrix(rnorm(400),ncol=8)  #sample size is 50
> data<-data.frame(data)
> names(data)<-c(paste("x",1:8,sep=""))  #8 independent 
> variables,x1-x8;
> #logistic regression model is logit(y)=x1+x2+x3+x4+x5+x6+x7+x8
> data$y<-exp(data$x1+data$x2+data$x3+data$x4+data$x5+data$x6+data$x7+data$x8)/(1+(data$x1+data$x2+data$x3+data$x4+data$x5+data$x6+data$x7+data$x8))
>
> logist<-glm(y~.,family=binomial(),data=simdata)
> *Warning messages:*
> 1: algorithm can't converge in: glm.fit(x = X, y = Y, weights = 
> weights,
> start = start, etastart = etastart,
> 2: the probability is 0 or 1 in: glm.fit (x = X, y = Y, weights = 
> weights,
> start = start, etastart = etastart,
> -- 
> With Kind Regards,
> Zhi Jie,Zhang ,PHD
> Department of Epidemiology
> School of Public Health
> Fudan University
>
> [[alternative HTML version deleted]]
>
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> 


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