On Jul 6, 2012, at 4:30 PM, Abraham Mathew wrote:
Ok, so let's say I have a logit equation outlined as Y= 2.5 + 3X1 +
2.3X2 +
4X3 + 3.6X4 + 2.2X5
So a one unit increase in X2 is associated with a 2.3 increase in Y,
Assuming, that is, you also understand what Y is. From you comments so
far, I have some nagging worries regarding your understanding of that
point.
--
David.
regardless of what the other
predictor values are. So I guess instead of trying to plot of curve
with
all the predictors accounted
for, I should plot each curve by itself.
I'm still not sure how to do that with so many predictors.
Any help would be appreciated.
On Thu, Jul 5, 2012 at 4:23 PM, Bert Gunter <gunter.ber...@gene.com>
wrote:
You have an about 11-D response surface, not a curve!
-- Bert
On Thu, Jul 5, 2012 at 2:39 PM, Abraham Mathew
<abmathe...@gmail.com>wrote:
I have a logit model with about 10 predictors and I am trying to
plot the
probability curve for the model.
Y=1 = 1 / 1+e^-z where z=B0 + B1X1 + ... + BnXi
If the model had only one predictor, I know to do something like
below.
mod1 = glm(factor(won) ~ as.numeric(bid), data=mydat,
family=binomial(link="logit"))
all.x <- expand.grid(won=unique(won), bid=unique(bid))
y.hat.new <- predict(mod1, newdata=all.x, type="response")
plot(bid<-000:250,predict(mod1,newdata=data.frame(bid<-
c(000:250)),type="response"),
lwd=5, col="blue", type="l")
I'm not sure how to proceed when I have 10 or so predictors in the
logit
model. Do I simply expand the
expand.grid() function to include all the variables?
So my question is how do I form a plot of a logit probability
curve when I
have 10 predictors?
would be nice to do this in ggplot2.
Thanks!
--
*Abraham Mathew
Statistical Analyst
www.amathew.com
720-648-0108
@abmathewks*
David Winsemius, MD
West Hartford, CT
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