[R] Plotting the probability curve from a logit model with 10 predictors
dwinsemius at comcast.net
Sat Jul 7 15:11:54 CEST 2012
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
> regardless of what the other
> predictor values are. So I guess instead of trying to plot of curve
> 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.berton at gene.com>
>> You have an about 11-D response surface, not a curve!
>> -- Bert
>> On Thu, Jul 5, 2012 at 2:39 PM, Abraham Mathew
>> <abmathewks at 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
>>> mod1 = glm(factor(won) ~ as.numeric(bid), data=mydat,
>>> all.x <- expand.grid(won=unique(won), bid=unique(bid))
>>> y.hat.new <- predict(mod1, newdata=all.x, type="response")
>>> lwd=5, col="blue", type="l")
>>> I'm not sure how to proceed when I have 10 or so predictors in the
>>> 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.
>>> *Abraham Mathew
>>> Statistical Analyst
David Winsemius, MD
West Hartford, CT
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