[R] glm(family=binomial(link=logit))

From: Robin Hankin <r.hankin_at_noc.soton.ac.uk>
Date: Sat 16 Jul 2005 - 01:00:44 EST


Hi

I am trying to make glm() work to analyze a toy logit system.

I have a dataframe with x and y independent variables. I have

L=1+x-y (ie coefficients 1,1,-1)

then if I have a logit relation with L=log(p/(1-p)), p=1/(1+exp(L)).

If I interpret "p" as the probability of success in a Bernouilli trial, and I can observe the result (0 for "no", 1 for "yes") how do I retrieve the coefficients c(1,1,-1) from the data?

n <- 300

des <- data.frame(x=(1:n)/n,y=sample(n)/n)   # experimental design
des <- cbind(des,L=1+des$x-des$y)            # L=1+x-y
des <- cbind(des,p=1/(1+exp(des$L)))         # p=1/(1+e^L)
des <- cbind(des,obs=rbinom(n,1,des$p))      # observation: prob of  
success = p.

My attempt is:

glm(obs~x+y,data=des,family=binomial(link="logit"))

But it does not retrieve the correct coefficients of c(1,1,-1) ; I would expect a reasonably close answer with so much data.

What is the correct glm() call to perform my logit analysis?

--
Robin Hankin
Uncertainty Analyst
National Oceanography Centre, Southampton
European Way, Southampton SO14 3ZH, UK
  tel  023-8059-7743

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Received on Sat Jul 16 01:07:07 2005

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