similar to: reference for logistic regression

Dear list Is there anywhere I could find further information on how to interpret the output for a logistic regression for validate() from Design package?. I tried ?validate and google but I cannot find information on what the rows and the columns represent. Thanks David

Dear list, this must be an easy one: I have a data.frame of two columns, "ID" with four different levels (A to D) and numerical "size", and each of the 4 different IDs is repeated a different number of times. I would like to get the mean size for each ID as another data.frame. I have tried the following: >ID= as.character(unique(data[,1])) # I use unique() because

Dear list, first apologies for this is not strictly an R question but a theoretical one. I have read that use of k-means clustering assumes sphericity of data distribution. Can anyone explain me what this means? My statistical background is too poor. Is it another kind of distribution, like gaussian or binomial? What does it happen if the distribution is not spherical? Could you give me an

Dear list I would like to compare two measurements of disease severity (M1 and M2), one of the is continuous (M1 ranging from 1 to 10) and the other is ordinal (M2 takes Low, Medium, high and very high). Do you think is ok to use cor() function to test whether the two agree, i.e correlate? I am afraid that if I set M2 to 1,2,3 and 4, the function cor() will take them as continuous and

Dear list, I have a data.frame with nine categorical variables (0,1,2 and NAs) that I would like to get the number of events for each of them. I can extract this using summary() for each variable at a time with the as.factor()argument (otherwise it will get me the mean value): >summary(as.factor(mydf[,3])) 0 1 2 NA's 194 67 4 2 Trying to use apply() to get this for

Dear list, I have a categorical variable in a data.frame that I would like to plot using a histogram to show number of events. Values are 0, 1 and some NAs. I can?t make the hist() function to 1) include a column with the number of NAs 2) have the x axis to be categorical, I always get 0, 0.2, 0.4,... 1 divisions Can anyone help me? This is my code. "database" is my data.frame and

Hi, I was wondering if someone could please help me. I am doing a logistic regression to compare size at maturity between 3 seasons. My model is: fit <- glm(Mature ~ Season * Size - 1, family = binomial, data=dat) where Mature is a binary response, 0 for immature, 1 for mature. There are 3 Seasons. The Season * Size interaction is significant. I would like to compare the size at 50%

Dear list, I have a text file from a scanner that includes 20 lines of text (scanner settings) before it actually starts showing the readings in a tabular format (headings are ID, intensity, background and few others). I am a biologist with some experience using R and my question is if it is possible to read this file into an R workspace and store the actual readings in a dataframe,

Full_Name: José Otero Version: Version 1.5.0 (2002-04-29) OS: Redhat 7.3 Submission from: (NULL) (192.187.16.164) Hi: Installation of package faraway as root, from tarbal: R CMD INSTALL ./faraway.tar.gz ERROR: cannot extract package from './faraway.tar.gz' idem, from zipped package: R CMD INSTALL faraway.zip gzip: faraway.zip has more than one entry--rest ignored ERROR: cannot

Dear all, I am trying to use the logistic regression with MCMClogit (package: MCMCpack/Coda) and I want to put a beta prior on the parameters, but it's giving me error message (please see output below) no matter what shape 1 or 2 I use. It works perfect with the cauchy or normal priors. Do you know if there is a catch there somewhere? Thanks logpriorfun <- function(beta,shape1,shape2){

Dear R- users and Helpers: I downloaded the package from www.stat.lsa.umich.edu/~faraway/book and installed it from local zip file. It looked fine. But when I input library(faraway) it showed " Error in library(faraway) : 'faraway' is not a valid package --- installed < 2.0.0? What I used is R 2.0.0 version now. What should I do? Thank you very much. Xin

I am just about working through Faraways excellent tutorial "practical regression and ANOVA using R" on page 24 he makes the x matrix: x <- cbind(1,gala[,-c(1,2)]) how can I understand this gala[,-c(1,2)])... I couldn't find an explanation of such "c-like" abbreviations anywhere. thanks for a hint. another problem: I couldn't load the faraway library, using the

Hi R community! I am analyzing the data set "motorins" in the package "faraway" by using the generalized additive model. it shows the following error. Can some one suggest me the right way? library(faraway) data(motorins) motori <- motorins[motorins$Zone==1,] library(mgcv) >amgam <- gam(log(Payment) ~ offset(log(Insured))+ s(as.numeric(Kilometres)) + s(Bonus) + Make +

Hi there, >library(faraway) >pima pregnant glucose diastolic triceps insulin bmi diabetes age test 1 6 148 72 35 0 33.6 0.627 50 1 2 1 85 66 29 0 26.6 0.351 31 0 >data(pima) >pima pregnant glucose diastolic triceps insulin bmi diabetes age test 1 6 148 72 35 0 33.6

Dear R-Help listers, I am trying to estimate an proportional odds logistic regression model (or ordered logistic regression) and then make predictions by supplying a hypothetical x vector. However, somehow this does not work. I guess I must have missed something here. I first used the polr function in the MASS package, and I create a data frame and supply it to the predict function (see below):

Is this text publicized? I ran across it doing an internet search. I have never seen any reference to it and it is not on CRAN under documentation. http://www.stat.lsa.umich.edu/~faraway/book/ -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or

Hello, I have compared the potentials of R and Stata about GLMM, analysing the dataset 'ohio' in the package 'faraway' (the same dataset is analysed with GEE in the book 'Extending the linear model with R' by Julian Faraway). Basically, I've tried the 2 commands 'glmmPQL' and 'glmer' of R and the command 'xtmelogit' of Stata. If I'm not

Dear all, I'm struggling to find the best (set of?) function(s) to do repeated measures logistic regression on some data from a psychology experiment. An artificial version of the data I've got is as follows. Firstly, each participant filled in a questionnaire, the result of which is a score. > questionnaire ID Score 1 1 6 2 2 5 3 3 6 4 4 2 ...

All I have been looking into the books on performing statistics in R, in particular I am interested in General Linear Mixed Models, for Randomized Complete Block Design Experiments The list I have come away with so far is: Mixed Effects Models in S and S-plus by Pinheiro (2002)

Faraway's book titled "Practical Regression and Anova using R", with full text available online at: http://cran.r-project.org/doc/contrib/Faraway-PRA.pdf refers to a data set, stat500, which compares midterm and final grades. It can be used to illustrate similar concepts. A google search for faraway.zip will locate the actual data. --- Date: Sun, 15 Feb 2004 10:37:08 -0800