How to predict using glm in R?

Question

So I have a glm that is defined like this

oring.glm = glm(oring.data$Damaged ~ oring.data$Temp, data = oring.data, family=binomial)

The data looks like this

Oring   Temp
1        15
0        20
1        30

I want to predict what happens to the Oring at a specific temperature

I've tried doing this

logodds = predict(oring.glm, list(Temp=31))

But this gives me a list of values, as opposed to a single odds value.

How do I get that?

If you adjust the formula to be `Damaged~Temp`, you'll get the expected behavior. — josliber, Mar 14 '14 at 02:58
Check the example in `?predict.glm` to see how to set up `newdata` argument. — Roman Luštrik, Mar 14 '14 at 08:17

score 0 · Answer 1 · answered Mar 15 '14 at 13:20

If I'm correct to assume that you DV is dichotomous, then I'd use the logit link function, and access the predicted value of my fit using simple indexing:

g=glm(y~x,family=binomial("logit")) #fit
predict(g)[1234] # gives the predicted value of y for the x=1234.

How to predict using glm in R?

1 Answers1