hello all
I am really confusing that how predict(,type = "terms",) gets the desired
result. For example,
sample <- matrix(nrow = 10, ncol = 2)
colnames(sample) <- c("y","x")
sample[,1] <- c(rep(1,times = 5), rep(0,times = 5))
sample[,2] <- c(1,1,0,1,1,0,1,0,0,1)
sample <- as.data.frame(sample)
s_model <- glm(y~x, data = sample, family = binomial(link = "logit"))
s_pred <- predict(s_model, type = "terms", sample)
print(s_pred)
x
1 0.7167038
2 0.7167038
3 -1.0750557
4 0.7167038
5 0.7167038
6 -1.0750557
7 0.7167038
8 -1.0750557
9 -1.0750557
10 0.7167038
attr(,"constant")
[1] -0.02355661
But, if i compute it by myself, i can't get the same result. Is the formula
like this:
scale(sample$x)*coef(s_model)[-1]
[,1]
[1,] 1.387891
[2,] 1.387891
[3,] -2.081836
[4,] 1.387891
[5,] 1.387891
[6,] -2.081836
[7,] 1.387891
[8,] -2.081836
[9,] -2.081836
[10,] 1.387891
attr(,"scaled:center")
[1] 0.6
attr(,"scaled:scale")
[1] 0.5163978
Can someone help me? Thank you!
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