[R] glm(family=binomial(link=logit))
Robin Hankin
r.hankin at noc.soton.ac.uk
Fri Jul 15 17:00:44 CEST 2005
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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