Dear Greg Snow I mean in the help documentation of predict.glm, the arguments of âtypeâ wrote that âThe "terms" option returns a matrix giving the fitted values of each term in the model formula on the linear predictor scale.â But I canât get the same result of the function if I computed like the documatation said! I just want to know if you can get the same result of the âpredict.glm(,âtermsâ)â if you compute by yourself? Thank you very much!!!
å件人: Greg Snow [mailto:538...@gmail.com] åéæ¶é´: 2013å¹´9æ19æ¥ 0:20 æ¶ä»¶äºº: å²³èµ æé: r-help 主é¢: Re: [R] the values of predict( , type = "terms", ) What do you get with: sample$x * coef(s_model)[-1] On Tue, Sep 17, 2013 at 3:09 AM, å²³èµ <yue...@139.com> wrote: hello all I am really confusing that how predict(,type = "terms",) gets the desired result. For example, sample <- matrix(nrow = 10, ncol = 2) colnames(sample) <- c("y","x") sample[,1] <- c(rep(1,times = 5), rep(0,times = 5)) sample[,2] <- c(1,1,0,1,1,0,1,0,0,1) sample <- as.data.frame(sample) s_model <- glm(y~x, data = sample, family = binomial(link = "logit")) s_pred <- predict(s_model, type = "terms", sample) print(s_pred) x 1 0.7167038 2 0.7167038 3 -1.0750557 4 0.7167038 5 0.7167038 6 -1.0750557 7 0.7167038 8 -1.0750557 9 -1.0750557 10 0.7167038 attr(,"constant") [1] -0.02355661 But, if i compute it by myself, i can't get the same result. Is the formula like this: scale(sample$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! [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Gregory (Greg) L. Snow Ph.D. 538...@gmail.com [[alternative HTML version deleted]]
______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
