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Version 1.3.1  (2001-08-31)

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> x <- rnorm(100)
> y <- 1 + x + rnorm(100)
> y <- as.integer(y<0)
> probitfit <- glm(y ~ x, family = binomial(link = probit))
> summary(probitfit)

Call:
glm(formula = y ~ x, family = binomial(link = probit))

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-1.6524  -0.5450  -0.1745   0.2880   2.4879  

Coefficients:
            Estimate Std. Error z value Pr(>|z|)    
(Intercept)  -1.2301     0.2413  -5.098 3.43e-07 ***
x            -1.8627     0.3689  -5.050 4.42e-07 ***
---
Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1 

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 116.652  on 99  degrees of freedom
Residual deviance:  68.169  on 98  degrees of freedom
AIC: 72.169

Number of Fisher Scoring iterations: 5

> index <- probitfit$coef[1] + probitfit$coef[2]*x
> invmills <- dnorm(index)/pnorm(index)
>