similar to: Omnibus main effects in summary.lme?

R 2.9.1 Windows XP I am fitting a random effects ANOVA with two factors Group which has two levels and Time which has three levels: fita<-lme(Post~Time+factor(Group)+factor(Group)*Time, random=~1|SS,data=blah$alldata) I want to get the omnibus significance tests for each factor and the interaction. I believe I can get the omnibus test for the interaction by running the model:

Dear all - I have followed the thread the reply to which was lead by Thomas Lumley about using pweibull to generate fitted survival curves for survreg models. http://tolstoy.newcastle.edu.au/R/help/04/11/7766.html Using the lung data set, data(lung) lung.wbs <- survreg( Surv(time, status)~ 1, data=lung, dist='weibull') curve(pweibull(x, scale=exp(coef(lung.wbs)),

Daniel, When Group is entered as a factor, and the factor has two levels, the ANOVA table gives a p value for each level of the factor. What I am looking for is the omnibus p value for the factor, i.e. the test that the factor (with all its levels) improves the prediction of the outcome. You are correct that normally one could rely on the fact that the model

Hi, I directed somebody to install R (2.6.1) on his OSX computer, following instructions from http://cran.r-project.org/bin/macosx. She can run R from the console. But plot(1:10) doesn't produce any output or open a window (as I am used to from linux). More importantly: Rscript is not in the path (minor problem ln -s is hopefully doable). I tried to put a hardcoded path to Rscript into the

If one estimates a model using multinom, is it possible to perform the omnibus LR test ( the analogue to omnibus F in linear models ) using the output from multinom ? The residual deviance is there but I was hoping I could somehow pull out the deviance based on just using an intercept ? Sample code is below from the CAR book but I wasn't sure how to do it based on that example. Thanks

I''ve noticed that the copy of Mongrel installed by the camping-omnibus gem doesn''t work with Ruby 1.8.6. Or to be more specific, cgi_multipart_eof_fix (which Mongrel is dependent upon) doesn''t work: > $ sudo gem install mongrel --source http://code.whytheluckystiff.net > > ERROR: Error installing mongrel: > cgi_multipart_eof_fix requires Ruby version

gem install camping-omnibus --source code.whytheluckystiff.net Considering the number of optional dependencies now in Camping, I''ve put together an eigengem which will load all of the recommended libraries that most devoted campers will want: ActiveRecord, Mongrel, SQLite3, RedCloth and the acts_as_versioned gem. (Those last two are used in the examples.) Stuff like mosquito and

I am looking for an R package with which one can calculate an effect size for a set of contrasts given an omnibus chi-square test statistic (more than 1 degree of freedom). Is there such a package? Presumably, it would implement the procedure (or something like it) described by Roznow and Rosenthal 1996 Psychological Methods 1: 331-340. many thanks! Steven Orzack Fresh Pond Research Institute

This is very possibly not a question on R. I was under the impression that the argument that gives rise to Fisher's LSD method in ANOVA works in other situations with three-way comparisons too, given that formal logic works the same ("if the omnibus test rejects, only two of the three groups may be equal, and therefore only one hypothesis can be rejected falsely"). However, when I

i am having problem running my own data. yesterday it was working just fine. today it is not. this is the code i was using as an example to follow. this code ALSO worked just fine yesterday, and is no longer working at all. i suspect it is a problem with either my computer or the software, at this point. if THIS won't even run.... something is wrong. i can assure you this isn't

r-help: I have an R package suggestion. After spending several hours the other day installing about a dozen packages, I had an idea. In xemacs, there is a "sumo" package which allows me to install a large bundle of xemacs packages at one time (about a 120 modes including ESS). I think R should have a similar bundle. It would be so much easier than hunting/downloading/installing.

Dear all Somebody may have asked this before but I could not find any answers in the web so let me ask a question on lme. When I have a fixed factor of, say, three levels (A, B, C), in which each level has different size (i.e. no. of observations; e.g. A>B>C). When I run an lme model, I get the same degree of freedom for all the contrast t-tests (e.g. AvsB or BvsC). I have tried this to

Hi all - R2.0.1, OS X Perhaps while there is some discussion of lme going on..... I am trying to execute a glmm using glmmPQL from the MASS libray, using the example data set from McCullagh and Nelder's (1989, p442) table 14.4 (it happens to be the glmm example for GENSTAT as well). The data are binary, representing mating success (1,0) for crosses between males and females from two

Hi all - R2.0.1 on OSX;MASS library;nlme library I am trying to emulate the solution to a problem set that has normally been run in Genstat, using R. The problem that I am having at the moment is with the following glmm question (using glmmPQL from the MASS library): "We have two different forest habitats (first rotation thicket, and high forest) which we want to survey for the

Hi all, I have a questions regarding mixed effects models: I'm trying to plot e.g. fitted vs residuals for each level of the random effects, and i'm getting the same error. I guess this might be a problem of the graphic capabilities of R. Is there any way to obtain those plots? library(nlme) attach(ergoStool) names(ergoStool) [1] "effort" "Type"

Hi, All, I am implementing real-time Rsync on Windows 2008 system. I set up Rsync server and Rsync client on two machines. An windows service is watching all the Windows file events with FileSystemWatcher. However, the service cannot tell the exactly what happened to folders such as create, delete, or modified. So, I ignored folder event, and only catch file changing events. After I catch

HI Dave, My comment was based? on: " >The main question with this test was if the interaction term is significant (i.e. growth rate). However, my question is could I also look at the p-values of the main effects to ?>say if body mass increase significant with body mass?" Here, the result shown were from the summary of the linear model.?? We report the p-values of the main

Hi all, I didn't get a response to my post of this issue a week ago, so I've tried to clarify: When I use lme to analyze a model of nested random effects, the variance estimates of levels higher in the hierarchy appear to have much more variance than they should. In the example below with 4 levels, I simulate variance in level 2 (sd=1.0) and level 4 (sd=0.1), but levels 1 and 3 do

Hi, Does anybody have a good tip of how to treat bimodal data to perform statistical analyses? My data set ranges from -1 to 1 (any values are posssible in between) and most data are either close to -1 or close to 1. They are the results of a two choice experiment where individuals could choose more than once in either direction and scores were calculated. Simone Simone Immler

I sent a bug report to Mozilla about this, but I was hoping someone here might have an insight on this. I use SeaMonkey as my default browser (32-bit even though I'm running x86_64 CentOS 5.1), version 1.1.7. Shortyl after installing 1.1.7 on my 5.0 (and even since 5.1), I noticed that every so often, seemingly at random, although it appears most frequently when I click on something that