thank you for your help
orkun wrote:
Hello
I try to find probability values of some predictor combinations using logistic reg. in response level.
Firstly I found coefficients by glm function.
Then I followed two ways to get probability values:
1- probility <- exp(X0+bX1+cX2+...)/((1+exp(X0+bX1+cX2+...))
2- probility <- predict(glm.obj,type="resp")
Should have these two given same result ? if so, I did not have. Why ?
Does anyone have any idea ?
This works for me. Are you sure you're getting the correct linear predictor in (1). Here's an example:
R> x = glm(y ~ trt + I(week > 2), data = bacteria, family = binomial) R> str(predict(x, type = "resp")) Named num [1:220] 0.944 0.944 0.823 0.823 0.900 ... - attr(*, "names")= chr [1:220] "1" "2" "3" "4" ... R> coef(x) (Intercept) trtdrug trtdrug+ I(week > 2)TRUE 2.8332455 -1.1186847 -0.6372255 -1.2948522 R> lp = model.matrix(x) %*% coef(x) R> str(exp(lp)/(1 + exp(lp))) num [1:220, 1] 0.944 0.944 0.823 0.823 0.900 ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:220] "1" "2" "3" "4" ... ..$ : NULL R>
Now one thing is clear to me: predict(x, type = "resp") gives probability values. For the sake of simplicity, I can choose it, instead of using first way.
cordially
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