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

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I am getting confused when i am trying to compare the results of Stata and R. I am using example given on the webpage http://www.ats.ucla.edu/stat/stata/webbooks/logistic/chapter2/default.htm First run the following command in Stata

use http://www.ats.ucla.edu/stat/stata/webbooks/logistic/apilog, 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 l开发者_C百科ink

https://spreadsheets.google.com/spreadsheet/ccc?key=0Ajt182RLsguldFlLQmd6Z1ZoczJCenJIdmREUkhxTFE&hl=en_US

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

Thanks in Advance.

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

library(foreign)
d1 <- read.dta('http://www.ats.ucla.edu/stat/stata/webbooks/logistic/apilog.dta')
m1 <- glm(hiqual~cred_hl + pared_hl + cred_hl*pared_hl,family=binomial,  data=d1)