similar to: Storing p-values from a glm

Hello I'm very new to R (which is excellent), so apologies if this has already been raised. In the spdep package, I'm trying to undertake an autoregressive mixed model using the lagsarlm function. This is working fine, but there does not appear to be a method of including an explanatory variable without it automatically being included as a lagged term. I'm after something along the

Dear List Apologies for such a simple question: I have a vector of 738 elements, coded with values between 1 and 16 (but not containing 7, 10, 11 or 13) and wish to recode value 14 to 1, 4 to 2, 1 to 3, 2 to 4 and all other values to 5. I've been trying to use the replace function (in base) and %in%, but without success. Many thanks Roy

Dear R-help I have two separate experiments, one a repeated-measures design, the other a split-plot. In a standard ANOVA I have usually undertaken a multiple-comparison test on a significant factor with e.g TukeyHSD, but as I understand it such a test is inappropriate for repeated measures or split-plot designs. Is it therefore sensible to use Helmert contrasts for either of these designs?

Hello I'm very much a beginner on meta-analysis, so apologies if this is a trivial posting. I've been sent a set data from separate experimental studies, Treatment and Control, but no measure of the variance of effect sizes, numbers of replicates etc. Instead, for each study, all I have is the mean value for the treatment and control (but not the SD). As far as I can tell, this forces

Hello, I'd like to use DBI to store lm objects in a database. I've to analyze many of linear models and I cannot store them in a single R-session (not enough memory). Also it'd be nice to have them persistent. Maybe it's possible to create a compact binary representation of the object (the kind of format created created by "save"), so that one doesn't need to write

Hello everyone, (This is my second question posted today on the R list). I am carrying out a competing risks analysis using the cuminc function...this takes the form: cuminc(ftime,fstatus,group) In my study, fstatus has 3 different causes of failure (1,2,3) there are also censored cases (0). "group" has two levels (0 and 1). I therefore have 6 different cumulative incidence curves:

Hello, I'm wondering what's the best way to analyse an unbalanced design with a low number of replicates. I'm not a statistician, and I'm looking for some direction for this problem. I've a 2 factor design: Factor batch with 3 levels, and factor dose within each batch with 5 levels. Dose level 1 in batch one is replicated 4 times, level 3 is replicated only 2 times. all

Dear Rgurus, To my knowledge the best way to visualize the distribution of a discrete variable X is plot(table(X)) The problem which I have is the following. I have to discrete variables X and Y which distribution I would like to compare. To overlay the distribution of Y with lines(table(Y)) gives not satisfying results. This is the same in case of using density or histogram. Hence, I am

Hello, I'm trying to reproduce some SAS result wit R (after I got suspicious with the result in R). I struggle with the contrasts in a linear model. I've got three factors > d$dose <- as.factor(d$dose) # 5 levels > d$time <- as.factor(d$time) # 2 levels > d$batch <- as.factor(d$batch) # 3 levels the data frame d contains 82 rows. There are 2 to 4 replicates of

Hi I have submitted a package (rioja) to CRAN. It checks OK for all R versions and OS's except r-release-macosx-ix86 where it fails when checking the examples. Specifically, it fails because R can't find the package vegan which is needed in a function. Here is the snippet from the check results: ### Begin snippet checking examples ... ERROR Running examples in 'rioja-Ex.R'

Hi I'm reading a CSV file using read.table, and it keeps importing a text variable as a factor. To overcome this, I've used the as.is command referring to the variable in question (called "stim") data<-read.table(file.choose(), header=T, sep=",", as.is = "stim") However, "stim" is still imported as a factor. I notice there are other read.table

Hello, I've a problem with a self written routine taking a lot of memory (>1.2Gb). Maybe you can suggest some enhancements, I'm pretty sure that my implementation is not optimal ... I'm creating many linear models and store coefficients, anova p-values ... all I need in different lists which are then finally returned in a list (list of lists). The input is a matrix with 84 rows

Hi Everybody, I am a newbie in R. I have a data in the form of a matrix which I want to make some 3D plots using R. There is some functions for instance hist() for 2D plots, but I cant find any function for 3D plots. Is there any function available in R for 3D plots? If so, is there any documention available on internet so that I can go through. With regards, Soumyadeep

Updating from centos 5.4 to 5.5 using an update rather than a rebuild, I get the following complaint from yum:- lvm2-2.02.56-8.el5_5.1.x86_64 from setup has depsolving problems --> Missing Dependency: device-mapper >= 1.02.39-1 is needed by package lvm2-2.02.56-8.el5_5.1.x86_64 (setup) This is from a local mirror, so checking the upstream feed in case the mirroring is incomplete I see

Using R (version 0.63.3) for MS windows, I try the following command > shell(paste("cd ",getenv("RHOME"),sep="")) which replies with an error message Too many parameters - FILES\RW0633 which appears to suggest that the space if the path name is causing difficulties to the cd command. getenv returns > getenv("RHOME") RHOME

Dear R-devlopers, I removed yesterday the R.2.1. installation from windows NT laptop and I am getting the following error when building a pacage with R.2.2 ---------- Making package msbase ------------ adding build stamp to DESCRIPTION making DLL ... make[3]: *** No rule to make target `d:/prog/r/rw2011/include/R.h', needed by `llogic.o'. Stop. .... I have no idea from where

> On Feb 3, 2020, at 2:50 PM, Nadav Amit <namit at vmware.com> wrote: > >> On Feb 3, 2020, at 8:34 AM, David Hildenbrand <david at redhat.com> wrote: >> >> On 03.02.20 17:18, Alexander Duyck wrote: >>> On Mon, 2020-02-03 at 08:11 -0500, Michael S. Tsirkin wrote: >>>> On Thu, Jan 30, 2020 at 11:59:46AM -0800, Tyler Sanderson wrote:

> On Feb 3, 2020, at 2:50 PM, Nadav Amit <namit at vmware.com> wrote: > >> On Feb 3, 2020, at 8:34 AM, David Hildenbrand <david at redhat.com> wrote: >> >> On 03.02.20 17:18, Alexander Duyck wrote: >>> On Mon, 2020-02-03 at 08:11 -0500, Michael S. Tsirkin wrote: >>>> On Thu, Jan 30, 2020 at 11:59:46AM -0800, Tyler Sanderson wrote:

Greetings, I have recently come into some confusion over weather or not AIC results for comparing among models requires that they be nested. Reading Burnham & Anderson (2002) they are explicit that nested models are not required, but other respected statisticians have suggested that nesting is a pre-requisite for comparison. Could anyone who feels strongly regarding either position

On 08.03.20 05:47, Tyler Sanderson wrote: > Tested-by: Tyler Sanderson <tysand at google.com> > > Test setup: VM with 16 CPU, 64GB RAM. Running Debian 10. We have a 42 > GB file full of random bytes that we continually cat to /dev/null. > This fills the page cache as the file is read. Meanwhile we trigger > the balloon to inflate, with a target size of 53 GB. This setup