Thanks to *Prof Brian Ripley* and *Dimitris Rizopoulos .*
Then it should be different for a linear model,e.g.y=x1+x2+...+x8
In logistic regression model,the y should be : data$y <- rbinom(length(p),
1, p)
But in  linear model, data$y<-x1+x2+...+x8+error, error~N(0,variance),
right?
It seems different between them(or it's also wrong for my simulated linear
model),i'm not very clear about them,thanks for a little more explanations
on them.


On 8/31/06, Prof Brian Ripley <ripley@stats.ox.ac.uk> wrote:
>
> On Thu, 31 Aug 2006, zhijie zhang wrote:
>
> > 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
>
> Rather it is logit(p) = ...,  and y ~ binomial(1, p)
>
> There is a different sort of 'logistic regression' with
>
> y = exp(eta)/(1+exp(eta)) + epsilon
>
> but you fit that by nls, not glm.
>
> >
> 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$x8))
>
> You need exp()/(1+exp()), and the second exp is missing.
>
> Once you have p, you can use data$y <- rbinom(length(p), 1, p)
>
> > 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,
>
> You do not have a Bernoulli response: it often helps to look at your
> simulated data to see if it makes sense (just as you would look at real
> data, I hope).
>
> --
> Brian D. Ripley,                  ripley@stats.ox.ac.uk
> Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
> University of Oxford,             Tel:  +44 1865 272861 (self)
> 1 South Parks Road,                     +44 1865 272866 (PA)
> Oxford OX1 3TG, UK                Fax:  +44 1865 272595
>



-- 
With Kind Regards,
Zhi Jie,Zhang ,PHD
Department of Epidemiology
School of Public Health
Fudan University

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