Hi Andrew,
My inclination would be to put all the variables in a data.frame
instead of putting the predictors in a matrix. But if you want to
continue down this road, you need to have a column named dat in a the
data.frame that contains a matrix. I couldn't figure out how to do
such a thing in a single call, so I had to create it in a separate
step:
newdat - data.frame(y=rep(NA, length(unique(x1
newdat$dat - cbind(unique(x1), x2=0)
p2a=predict(mod2, type=response, newdata=newdat)
p2a
Hope it helps,
Ista
On Sun, Sep 26, 2010 at 4:38 AM, Andrew Miles rstuff.mi...@gmail.com wrote:
I'm trying to get predicted probabilities out of a regression model, but am
having trouble with the newdata option in the predict() function. Suppose
I have a model with two independent variables, like this:
y=rbinom(100, 1, .3)
x1=rbinom(100, 1, .5)
x2=rnorm(100, 3, 2)
mod=glm(y ~ x1 + x2, family=binomial)
I can then get the predicted probabilities for the two values of x1, holding
x2 constant at 0 like this:
p2=predict(mod, type=response, newdata=as.data.frame(cbind(x1, x2=0)))
unique(p2)
However, I am running regressions as part of a function I wrote, which feeds
in the independent variables to the regression in matrix form, like this:
dat=cbind(x1, x2)
mod2=glm(y ~ dat, family=binomial)
The results are the same as in mod. Yet I cannot figure out how to input
information into the newdata option of predict() in order to generate the
same predicted probabilities as above. The same code as above does not
work:
p2a=predict(mod2, type=response, newdata=as.data.frame(cbind(x1, x2=0)))
unique(p2a)
Nor does creating a data frame that has the names datx1 and datx2, which
is how the variables appear if you run a summary() on mod2. Looking at the
model matrix of mod2 shows that the fitted model only shows two variables,
the dependent variable y and one independent variable called dat. It is
as if my two variables x1 and x2 have become two levels in a factor variable
called dat.
names(mod2$model)
My question is this: if I have a fitted model like mod2, how do I use the
newdata option in the predict function so that I can get the predicted
values I am after? I.E. how do I recreate a data frame with one variable
called dat that contains two levels which represent my (modified)
variables x1 and x2?
Thanks in advance!
Andrew Miles
Department of Sociology
Duke University
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Ista Zahn
Graduate student
University of Rochester
Department of Clinical and Social Psychology
http://yourpsyche.org
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and provide commented, minimal, self-contained, reproducible code.
