similar to: Olmstead-Tukey Diagram

Dear Evelina Ballato, ? Tue, 30 Apr 2024 10:36:32 +0000 Evelina Ballato <evelball at arpa.piemonte.it> ?????: > In the Openair package it is possible to restore the import csv file > function? This question is best addressed to the maintainer of the package (see the output of maintainer("openair")) if not to their GitHub issues at

In the Openair package it is possible to restore the import csv file function? it has been removed in the latest versions. Infinitely grateful Evelina Ballato Evelina Ballato Arpa Piemonte Dipartimento Territoriale Piemonte Nord Est - sede di Omegna ************************************************************************ Riservatezza/Confidentiality Ai sensi del Regolamento UE 679/2016, del

Arnaud: I just wanted to chime in here to say that getting these TrippLite USB UPS's supported under a NUT driver would be fantastic! They are simple, inexpensive UPS's (under $100 for 1000VA at Costco) and it would be quite the "deal of the year" to be able to buy these units so cheaply and monitor them directly via Linux. I already have 5 of these units and have

Colleagues, please help me with the simple question. How can I find R2 and p while doing best subsets regression? Also how can I see B and p for coefficients? Maybe you can advice me detailed manual, because in manual for the package this is not described. Thank you

i just purchased a tripp lite OMNIVS1500XL and have been attempting to get it working with the usb drivers since it doesn't have a serial port. it hasn't been anywhere near successful and i was hoping someone might be able to point me in the right direction. i run gentoo and this is what i currenlty have installed: nut 2.0.2 libusb 0.1.10a (gentoo modified) usbutils 0.11-r5

Hi, sorry but I can't found where the profiling data (llvmprof.out[?]) is generated. Perhaps soembody has a hint for me? Thank you very much Nico

On Wed, 1 Nov 2006, Nico Moser wrote: > sorry but I can't found where the profiling data (llvmprof.out[?]) is > generated. Perhaps soembody has a hint for me? Take a look at how the llvm/utils/profile.pl script works. -Chris -- http://nondot.org/sabre/ http://llvm.org/

Hi, On Nov 1, 2006, at 7:31 PM, Chris Lattner wrote: > On Wed, 1 Nov 2006, Nico Moser wrote: >> sorry but I can't found where the profiling data (llvmprof.out[?]) is >> generated. Perhaps soembody has a hint for me? > > Take a look at how the llvm/utils/profile.pl script works. In this script the lli command get the load-argument "somewhere/ profile_rt.so".

Hi everyone, I woudl like to apply a Tukey post hoc after a repeated measure ANOVA. I followed the suggestions that I found in this help -list especially this one: /[R] Tukey HSD (or other post hoc tests) following repeated measures ANOVA You want to use lme() in package nlme, then glht() in the multcomp package. This will give you multiplicity adjusted p-values and confidence intervals.

Dear Colleagues, I fit this model: mod1 <- lmer(x~category*comp+(1|id),data=impchiefsrm) where category has 4 levels and comp has 8 levels. These work: glht(mod1, linfct=mcp(category="Tukey") glht(mod1, linfct=mcp(comp="Tukey") What I'd like is (conceptually): glht(mod1, linfct=mcp(category:comp="Tukey") but it gives a syntax error. Any help is

Hi everybody! Can anybody help me to find an R-function for the Siegel-Tukey test. Than you in advance. Ralf Finne SYH, University of Applied Sciences Vasa Finland

Dear all, I have a serious problem in applying Tukey post hoc after a repeated measure ANOVA. I followed the suggestions that I found in this help -list especially this one: //[R] Tukey HSD (or other post hoc tests) following repeated measures ANOVA You want to use lme() in package nlme, then glht() in the multcomp package. This will give you multiplicity adjusted p-values and confidence

Hello, I am a little out of date and am still using S-Plus instead of R. I haven't been able to find the right place to ask this question, so I thought I would ask it here and hope that someone can help. I am unable to located the TukeyHSD() function in S-Plus. I have been able to use the GUI to run Tukey's test, but the results don't provide a p-value. Does anyone know how I can

hey, how can i extract the values from the CI's when i use following code for a tukey test? the output shows three CI's and i know it should work with 'names but i don't really know how... thanks library(multcomp) data1$soort<-as.factor(data1$soort) amod<-aov(waarde~soort,data=data1) g<-glht(amod, linfct=mcp(soort = "Tukey")) confint(g) -- View this message in

Hello R friends, I am looking for a function to perform the Siegel-Tukey test in R. Can anyvbody help me? Thanks so much! J. Hedderich -- --------------------------------------------------------------- Dipl. Inform. J. Hedderich Institut f??r Medizinische Informatik und Statistik im Klinikum S.H. - Campus Kiel - Phone : 0431/5973182 Brunswiker Str.

Hi. I was looking for help on how to use Tukey multiple comparison on Type III SS because I read on Quick R that it is using Type I SS by default. I am wondering if the use of glht helps. Thanks for help. Vera

Hi, I was wondering if you could help me: The following are the first few lines of my data set: subject group condition depvar s1 c ver 114.87 s1 c feet 114.87 s1 c body 114.87 s2 c ver 73.54 s2 c feet 64.32 s2 c body 61.39 s3 a ver 114.87 s3 a feet 97.21 s3 a body 103.31 etc. I entered the following ANOVA command: >dat <- read.table("mydata.txt", header=T)

Hi there, ============================= x=c(145,40,40,120,180, 140,155,90,160,95, 195,150,205,110,160, 45,40,195,65,145, 195,230,115,235,225, 120,55,50,80,45 ) y2=c( rep(as.character(1),5), rep(as.character(2),5), rep(as.character(3),5), rep(as.character(4),5), rep(as.character(5),5), rep(as.character(6),5) ) crd2=data.frame(x,y2) model1=aov(x~y2,data=crd2) TukeyHSD(model1)

dear all effect of a, b and c on d, total 48 comparisons, got one anova result in model1=aov(d~A*B*C). can we get all the result in one command? or can we interpret the whole comparisons from this result? how it work in Tukey HSD? jose ____________________________________________________________________________________ Access over 1 million songs.

I am trying to decipher, via post hoc test (Tukey), which of my sites differ from eachother. I have 4 sites, 2 sets of In vs Out (MPA) in separate Regions. Therefore my Mixed Effects Model code has 2 fixed effects: CB.lme <- lme(AsinCB~ In_Out*Region, random = (~1| site.trans/Quadrat) , data = Subsampled_props, control = lmeControl(maxIter = 500, msMaxIter = 500, msMaxEval = 500))