[R] Questions about Probit Analysis
Allan Engelhardt
allane at cybaea.com
Wed Nov 17 15:43:59 CET 2010
Sorry I am a bit late to this discussion, but I can't see if you ever
got an answer. Anyhow, on your first question:
On 31/10/10 19:14, Lorenzo Isella wrote:
> Dear All,
> I have some questions about probit regressions.
> I saw a nice introduction at
>
> http://bit.ly/bU9xL5
>
> and I mainly have two questions.
>
> (1) The first is almost about data manipulation. Consider the
> following snippet
>
> [...]
> mydata <- read.csv(url("http://www.ats.ucla.edu/stat/r/dae/binary.csv"))
> names(mydata) <- c("outcome","x1","x2","x3")
>
> myprobit <-
> glm(mydata$outcome~mydata$x1+mydata$x2+as.factor(mydata$x3),
> family=binomial(link="probit"))
> [...]
> #Now assume I can make a regression only on x1
>
>
> myprobit2 <- glm(mydata$outcome~mydata$x1,
> family=binomial(link="probit"))
> [...]
> Finally, I generate the data frame mydatanew (see some of its entries
> below)
>
> > mydatanew
> x1 successes failures
> 1 220 0 1
> 2 300 1 2
> 3 340 1 3
> 4 360 0 4
> 5 380 0 8
> [...................]
>
> where for every value of x1 I count the number of 0 and 1 outcomes
> (namely number of failures and number of successes). [...] How can I
> actually feed R with mydatanew to perform again a logistic regression
> on x1 only?
myprobit3 <- glm(cbind(successes, failures) ~ x1,
family=binomial(link="probit"), data = mydatanew )
all.equal(coef(myprobit2), coef(myprobit3), check.attributes = FALSE)
# [1] TRUE
Your second question we could discuss offline: it is not really an R
question, but you might want to have a look at something like the MNP
and perhaps survey packages.
Hope this helps a little.
Allan
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