[R] Specifying Prior Weights in a GLM
Enrique Garcia
eckomorph at yahoo.com
Sat Dec 11 17:59:15 CET 2010
Hello R folks,
I have three questions. I am trying to run a logistic regression (binomial
family) where the response variable is a proportion. According to R
Documentation in "a binomial GLM prior weights are used to give the number
of trials when the response is the proportion of successes." However when I
run my code I get the following error message:
Error in model.frame.default(formula = PER_ELA ~ A_EX + COMM + ENG + S_R +
:
variable lengths differ (found for '(weights)')
I'm not sure what I am doing wrong. My response variable is Y/M, which is
the proportion of 1's (successes) among M binary responses. My prior weight
is a variable indicating the number of trials for each observation.
This is an abbreviated version of the code that I ran:
glm1<-glm(PER_ELA~A_EX .... PER_LEA,
family=binomial(link="logit"),data=data2,weights="REG")
Question 1 and 2:
Does the number of trials for each observation in my dataset have to be the
same? What am I doing wrong here?
Question 3:
Is it OK for me to use percentages as predictor variables in a logistic
regression?
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