[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


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:


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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