similar to: glht (multicomparisons) with an interaction factor

Hi, I've got this model and following Hothorn et al advices, I used glht for a post hoc comparison > modezqM<-glm(rojos~estacion*zona3,quasipoisson,subset=(edadysexo=="M")) > anova(modezqM,test="F") Df Deviance Resid. Df Resid. Dev F Pr(>F) NULL 293 41148

I've read something about this problem, but I don't know how can i avoid this problem. Why the order of the factors give different results? I suppose it's because the order of the factors, i've just changed "lcc" from the first position to the last in the model, and the significance change completely >

Hi, I,ve a run a model like this mcrm<-glm(catroj~month,binomial) being catroj a binary response variable with two levels (infected and non infected) > anova(mcrm3,test="Chisq") Df Deviance Resid. Df Resid. Dev P(>|Chi|) NULL 520 149.81 mes 3 16.86 517 132.94 0.0007551 *** When I?m trying to do a post

I've run an ancova, edadysexo is a factor with 3 levels,and log(lcc) is the covariate (continous variable) I get this results > ancova<-aov(log(peso)~edadysexo*log(lcc)) > summary(ancova) Df Sum Sq Mean Sq F value Pr(>F) edadysexo 2 31.859 15.9294 803.9843 <2e-16 *** log(lcc) 1 11.389 11.3887 574.8081 <2e-16 ***

Hi, I have data with binomial response variable (survival) and 2 categorical independent variables (site and treatment) (see below).? I have run a binomial GLM and found that both IVs and the interaction are significant.? Now I want to do a post-hoc test for all pairwise comparisons to see which treatment groups differ.? I tried the glht function in the multcomp package, but I get surprising

I've made fligner test with the same data, changing the orders of the variables, and this what i get > fligner.test(rojos~edadysexo*zona*ano*estacion) Fligner-Killeen test of homogeneity of variances data: rojos by edadysexo by zona by ano by estacion Fligner-Killeen:med chi-squared = 15.7651, df = 2, p-value = 0.0003773 > fligner.test(rojos~ano*edadysexo*zona*estacion)

Hi, I'm trying to make a model in order to know wich factors got?s influence in the intensity of a infection, but just in the individuals who's got this infection. In my data I've got a variable called "prevalence" with 2 levels: 1.- Infected individual 0.- Non infected So what i'm trying to do is a subset in a model like this,

Hello everyone, Like a lot of people, I have been looking for functions in R doing ANOVA (ok) and performing multicomparisons (like Student-Newman-Keuls, etc.). As I have been a little bit disappointed, I have bee looking through the net for such "open source" softwares. I found one in: http://www.statpages.org/miller/openstat/OS4.html I have begun to use it, and it seems good and

Hi, I'm working with R in windows and I wonder if there is any command (of the kind CTRL+ ) to transfer the commands I've worked with (like: > model<-glm(prevalencia~edadysexo*mes*zona,binomial)) to a script automatically, without the results I received from R after execute them. Another question, what's the combination of CTRL+ for transfer the orders in the other way, fom the

Hi When i ran the below command on vicidial dialer: [root@vicidial2 ~]# tethereal -i eth0 -a duration:300 -w sample.cap Capturing on eth0 320167 147496 packets dropped on net i found: When i ran Acterna PVA-1000 on sample.cap it showed Max Jitter about 20 % and packet loss and echo as major cause of voice degradation. MQS was also less 2.59 where as it should be around 5.0. are packets being

Hi dears, I do > CHOL<-lme(chol~rt*cd4+sex+age+rf+nadir+pharmac+factor(hcv)+factor(hbs)+ haartd+hivdur+factor(arv), random= ~rt|id, na.action=na.omit) ...runs sweet,..then ....try a multicomparisons approach for the categorical rf > summary(glht(CHOL, linfct=mcp(rf="Tukey"))) * Error in model.frame.default(object, data, xlev = xlev) : l'oggetto non è una matrice

Hi all: I have a question about multi-comparison. The data is in the attachment. My purpose: Compare the predicted means of the 3 methods(a,b,c) pairwisely. I have 3 ideas: #idea1 result_aov<-aov(y~ method + x1 + x2) TukeyHSD(result_aov) diff lwr upr p adj b-a 0.845 0.5861098 1.1038902 0.0000001 c-a 0.790 0.5311098 1.0488902 0.0000002 c-b -0.055 -0.3138902

Hello list. I'm trying to rebuild the 2.6.9.67.0.20.EL kernel, but it fails even without modifications. How did I try it? Created a (non-root) build environment (not a mock ) Installed the kernel.scr.rpm and did a rpmbuild -ba --target=`uname -m` kernel-2.6.spec 2> prep-err.log | tee prep-out.log The build failed at the end: Processing files: kernel-xenU-devel-2.6.9-67.0.20.EL Checking

Signed-off-by: Scott Seago <sseago at redhat.com> --- AUTHORS | 17 ++++++ README | 10 +++ conf/ovirt-agent | 12 ++++ conf/ovirt-db-omatic | 12 ++++ conf/ovirt-host-browser | 12 ++++