What do you get with:
sample$x * coef(s_model)[-1]
On Tue, Sep 17, 2013 at 3:09 AM, 岳赟 <yueyun@139.com> wrote:
> hello all
>
> I am really confusing that how predict(,type = "terms",) gets the
desired
> result. For example,
>
> sample <- matrix(nrow = 10, ncol = 2)
>
> colnames(sample) <- c("y","x")
>
> sample[,1] <- c(rep(1,times = 5), rep(0,times = 5))
>
> sample[,2] <- c(1,1,0,1,1,0,1,0,0,1)
>
> sample <- as.data.frame(sample)
>
> s_model <- glm(y~x, data = sample, family = binomial(link =
"logit"))
>
> s_pred <- predict(s_model, type = "terms", sample)
>
> print(s_pred)
>
> x
>
> 1 0.7167038
>
> 2 0.7167038
>
> 3 -1.0750557
>
> 4 0.7167038
>
> 5 0.7167038
>
> 6 -1.0750557
>
> 7 0.7167038
>
> 8 -1.0750557
>
> 9 -1.0750557
>
> 10 0.7167038
>
> attr(,"constant")
>
> [1] -0.02355661
>
>
>
> But, if i compute it by myself, i can't get the same result. Is the
formula
> like this:
>
> scale(sample$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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>
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>
--
Gregory (Greg) L. Snow Ph.D.
538280@gmail.com
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