similar to: factorial function

Hi, I am trying to convert a colleague from using SPSS to R, but am having trouble generating a result that is similar enough to a bootstrapped cox regression analysis that was run in SPSS. I tried unsuccessfully with bootcens, but have had some success with the bootcov function in the rms package, which at least generates confidence intervals similar to what is observed in SPSS. However, the

Hi all, I had some trouble in?regrouping factor levels for a variable. After some experiments, I have figured out how I can recode to modify the factor levels. I would now like some help to understand why some methods work and others don't. Here's my code : rm(list=ls()) ###some trials in recoding factor levels char<-letters[1:10] fac<-factor(char) levels(fac) print(fac) ##first

Hi, I wish to compute multivariate test statistics for a within-subjects repeated measures design with anova.mlm. This works great if I only have two factors, but I don't know how to compute interactions with more than two factors. I suspect, I have to create a new "grouping" factor and then test with this factor to get these interactions (as it is hinted in R News 2007/2), but

Hello, I am trying to plot two sets of boxplots together. These are estimates of two experiments and?seven?factors. The results of the two experiments I want to plot as boxplots stacked to each other. Therefore I plot first the results of the first experiment; and next with the add option the second set of boxplots. The boxplots are plotted at 'at = 1:7 - 0.15 for the first experiment and

Dear List, I am using function recode, from package car, within sapply, as follows: L3 <- LETTERS[1:3] (d <- data.frame(cbind(x = 1, y = 1:10), fac1 = sample(L3, 10, replace=TRUE), fac2 = sample(L3, 10, replace=TRUE), fac3 = sample(L3, 10, replace=TRUE))) str(d) d[, c("fac1", "fac2")] <- sapply(d[, c("fac1", "fac2")], recode, "c('A',

Dear All, We are about to purchase the second edition of Agresti's "Categorical Data Analysis" (my old copy of the first ed. of that wonderful book is falling apart). I would appreciate suggestions about other comparable books which, if possible, have examples using R/S code (instead of SAS). Thanks, Ram?n -- Ram?n D?az-Uriarte Bioinformatics Unit Centro Nacional de

To anyone who can help, I have two stupid questions, and one fairly intelligent question Stupid question (1): is there an R function to calculate a factorial of a number? That is...is there a function g(.) such that g(3) = 6, g(4) = 24, g(6) = 720, etc? Stupid question (2): how do you extract the estimated covariance matrix of the random effects in an lme object? Intelligent question

Dear R Users, I am trying to write a wrapper around summarize and xYplot from Hmisc and am having trouble understanding how to pass arguments from the function I am writing to the nested functions. There must be a way, but I have not been able to figure it out. An example is below. Any advice would be greatly appreciated. Thanks, Dan # some example data df=expand.grid(rep=1:4,

Hey, hopefully there is an easy way to solve my problem. All that i think off is lengthy and clumsy. Given a data.frame d with columns VALUE, FAC1, FAC2, FAC3. Let FAC1 be something like experiment number, so that there are exactly the same number of rows for each level of FAC1 in the data.frame. Now i would like to scale all values according to the center of its experiment. So i can apply s

Hello, I'm trying to write code for a repeated measures ANOVA. To put things in perspective, I'll describe my experiment (briefly). I have a 2X2 factorial design with pH (5.5, 6.5) and local community (present, absent) as my treatments. I had plastic enclosures that I sampled across five weeks with the density of 7 species acting as my response variables. I'm analyzing one

R version 2.10.1 (2009-12-14) Copyright (C) 2009 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. Natural language support but running in an English locale R is a collaborative project with

Hi there; I have the following problem --- Xemacs cannot correctly parse a path to file when I load it. I have the following error, reported by Xemacs: from ess-parse-errors: Error in file(file, "r") : cannot open file `u:US-mortalityjuttalexible.r While the correct file path should be: u:\US-mortality\jutta\flexible.r Any ideas? Many thanks for your help. -Serge

Hi all, I would like to do some QSAR analysis (quantitative structure activity relationship). I need to use some Partial Least Squares (PLS) regression, but I have not seen this option on the R-project. Is it possible to do this kind of regression on R? thank you in advance best regards, olivier [[alternate HTML version deleted]]

Hi All, Sorry if this is a repost (a quick browse didn't give me the answer). I wonder if there are packages that can do the feature selection and classification at the same time. For instance, I am using SVM to classify my samples, but it's easy to get overfitted if using all of the features. Thus, it is necessary to select "good" features to build an optimum hyperplane (?).

Ich habe in R eine Version von SIR gefunden und ausprobiert. Leider kann diese multivariate Responses nicht verarbeiten. Gibt es in R eine ausgefeilte Version von SIR?

Dear All, I have been using the randomForest package for a couple of difficult prediction problems (which also share p >> n). The performance is good, but since all the variables in the data set are used, interpretation of what is going on is not easy, even after looking at variable importance as produced by the randomForest run. I have tried a simple "variable selection"

To avoid angry replies, let me first say that I know that the use of Type III sums of squares is controversial, and that some statisticians recommend instead that significance be judged using the non-marginal terms in the ANOVA. However, given that type III SS is also demanded by some… is there a function (equivalent to drop1 for lm) to obtain type III sums of squares for mixed models using the

Hi, I looked for the nls() function and couldn't find it. In the refman.pdf it's mentioned as part of the nls package which I cannot find and I also read something about the MASS package, also impossible to find for me. Kris -- ------------------------------------------------------------------------ http://perswww.kuleuven.ac.be/~u0027178/VCard/mycard.php?name=krisn

Hi, I have a microarray matrix 3000x70 for example (genes x experiments). This data has more than 2 classes. I would like to make some filtering on the genes. For example, I would like to exclude genes with the same mean expression across all classes. This is a problem of ANOVA H0:mu1=mu2=...=muk H1: at least one is different First question: Do you think Anova is reasonable for this? Second

How can I specify the maximum number of iterations in coxph whilst also specifying my model?? I can't find any on-line examples. Thanks