Reputation: 12856
I ran a logit model and am trying to plot the probability curve. I'm posting the question here and not the stats board because it's more an R question than a stats on, or at least I think so.
My model looks like:
mod1 = glm(factor(status1) ~ our_bid1 + factor(state) + factor(type),
data=mydat, family=binomial(link="logit"))
print(summary(mod1))
Status1
is a factor with two levels, our_bid
ranges from 0 to 20, state is 11 levels (top 10 populous and one which is other), and type has three levels.
To get the predicted probabilities, I ran the following code
all.x1 <- expand.grid(status1=unique(status1), our_bid1=unique(our_bid1),
state=unique(state), type=unique(type))
y.hat.new1 <- predict(mod1, newdata=all.x1, type="response")
The problem happens when I am trying to plot the curve. I'm trying to have a general curve for change in our bid given the model.
plot(our_bid1<-000:1600,
predict(mod1, newdata=data.frame(our_bid1<-c(000:1600)), type="response"),
lwd=5, col="blue", type="l")
Error in model.frame.default(Terms, newdata, na.action = na.action, xlev = object$xlevels) :
variable lengths differ (found for 'factor(state)')
In addition: Warning message:
'newdata' had 1601 rows but variable(s) found have 29532 rows
Do I have to specify all the independent variables in the plot command? What am I doing wrong?
Upvotes: 0
Views: 434
Reputation: 226587
mydata
)<-
and =
(which are not quite interchangeable, although they are in the context of assignment): you want something like(I need some text here so SO will format the code properly)
bidvec <- 0:1600
plot(bidvec,predict(mod1,
newdata=data.frame(our_bid1=bidvec,
state=ref_state,type=ref_type),
type="response"),
lwd=5, col="blue", type="l")
Upvotes: 3