Stata and R results not matched in Logistic Regression with two categorical predictors and their interaction

I am getting confused when i am trying to compare the results of Stata and R. I am using example given on the webpage First run the following command in Stata

use, clear

and then use following commands given in the section (2.2.2 A 2 by 2 Layout with Main Effects and Interaction)

generate cred_ed = cred_hl*pared_hl logit hiqual cred_hl pared_hl cred_ed

These two command will produce the results given on the webpage.

And then i have used following R code to reproduce same example

Data<- read.csv("Book1.csv",header=T) data.glm<-glm(hiqual~cred_hl + pared_hl + cred_hl*pared_hl,family=binomial, data=Data) summary(data.glm)

But results are not matched!

Data file for R can be download from following link

Note: Results for model with only main effects are matched but when we include interaction, it is not matched.

Thanks in Advance.


They give the same results to me (using ucla's data).

d1 <- read.dta('')
m1 <- glm(hiqual~cred_hl + pared_hl + cred_hl*pared_hl,family=binomial, data=d1)

Category:r Time:2011-08-12 Views:0
Tags: stata glm

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