Does the following help you:
library(MASS)
set.seed(1)
x1 <- rep(1:2, 2)
x2 <- rep(1:2, each=2)
DF <- data.frame(x1=x1, x2=x2, y=rbinom(4, 1000,
prob=(x1+x2-1.5)/3)/1000)
fit0 <- glm(y~1, family=binomial, data=DF,
weights=rep(1000, 4))
stepAIC(fit0, y~x1+x2)
spencer graves
Bernardo Rangel Tura wrote:
> Hi R-masters!
>
> I have a problem and need your help.
> I have 9 discrete variables with 2 levels each.
> In exploratory analisys I generate one matrix with chi-square for tables
> with 2 ariables each with this script
>
> setwd("F:/")
> dados<-read.csv("log.csv")[,2:10]
> dados.x<-matrix(NA,ncol=9,nrow=9)
> for(i in 1:8){
> for(j in (i+1):9){
> tab<-table(dados[,i],dados[,j])
> dados.x[i,j]<-round(as.numeric(chisq.test(tab)$statistic),3)
> dados.x[j,i]<-round(as.numeric(chisq.test(tab)$statistic),3)
> }
> }
> dados.x
>
> The result is:
>
> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
> [1,] NA 3.589 6.351 3.957 4.269 0.851 2.955 1.188 1.975
> [2,] 3.589 NA 9.664 24.596 12.510 26.284 8.580 3.608 6.574
> [3,] 6.351 9.664 NA 25.054 10.300 12.189 19.811 0.192 11.744
> [4,] 3.957 24.596 25.054 NA 50.032 35.587 22.401 1.950 26.631
> [5,] 4.269 12.510 10.300 50.032 NA 80.876 54.954 0.127 61.573
> [6,] 0.851 26.284 12.189 35.587 80.876 NA 57.346 0.741 49.738
> [7,] 2.955 8.580 19.811 22.401 54.954 57.346 NA 1.520 80.615
> [8,] 1.188 3.608 0.192 1.950 0.127 0.741 1.520 NA 0.311
> [9,] 1.975 6.574 11.744 26.631 61.573 49.738 80.615 0.311 NA
>
> Now I need fit a loglinear model with this variables, but I need know have
> a command with generate ALL models with the set this 8 vairables (ALL minus
> [,8]) incluindind the interactions.
>
> Can Anyone Help me?
>
>
>
> Thanks in advance
>
> Bernardo Rangel Tura, MD, MSc
> National Institute of Cardiology Laranjeiras
> Rio de Janeiro Brazil
>
>
--
Spencer Graves, PhD
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