search for: glht

Hi, I am experimenting with using glht() from multcomp package together with coxph(), and glad to find that glht() can work on coph object, for example: > (fit<-coxph(Surv(stop, status>0)~treatment,bladder1)) coxph(formula = Surv(stop, status > 0) ~ treatment, data = bladder1) coef exp(coef) se(coef...

...c comparisons on my lme model. I had originally planned to use Tukey HSD method as I am interested in all possible comparisons between my treatment levels. TukeyHSD, however, does not work with lme. The only other code that I was able to find, and which also seems to be widely used, is glht specified with Tukey: summary(glht(model, linfct=mcp(Treatment="Tukey"))) Out of curiosity, I ran TukeyHSD and the glht code for a simple ANOVA and found that they had quite different p-values. If the glht code is not running TukeyHSD, what does the "Tukey" in the code sp...

Hi, I want to export the result of glht in R into a LaTeX table, such as that result: Linear Hypotheses: Estimate Std. Error z value Pr(>|z|) Group1 - Group2 == 0 -0.14007 0.01589 -8.813 <0.001 "***" Group1 - Group3 == 0 -0.09396 0.01575 -5.965 <0.00...

Hi, I am trying to test some contrasts, using glht() in multcomp package on fixed effects in a linear mixed model fitted with lme() in nlme package. The command I used is: ## a simple randomized block design, ## type is fixed effect ## batch is random effect ## model with interaction dat.lme<-lme(info.index~type, random=~1|batch/ty...

Dear R members, I tried to fit an lme model and to use the glht function of multcomp. However, the glht function gives me some errors when using weights=varPower(). The glht error makes sense as glht needs factor levels and the model works fine without weights=. Does anyone know a solution so I do not have to change the lme model? Thanks Sibylle --&gt...

Hi, I have been trying glht() from multcomp package and contrast() from contrast package to test a contrast that I am interested in. With the following simulated dataset (fixed effect "type" with 3 levels (b, m, t), and random effect "batch" of 4 levels, a randomized block design with interaction), somet...

Using a factor with 'number' levels the straightforward symbolic formulation of a contrast in 'glht' of the 'multcomp' package fails. How can this problem be resolved without having to redefine the factor levels? Example: #A is a factor with 'number' levels #B similar factor with 'letter' levels dat<-data.frame(y=1:4,A=factor(c(1,1,2,2)), B=...

Hi all: There's a question about glht function. My data:data_ori,which inclue CD4, GROUP,time. f_GROUP<-factor(data_ori$GROUP) f_GROUP is a factor of 3 levels(0,1,2,3) result <- lme(sqrt(CD4) ~ f_GROUP*time ,random = ~time|ID,data=data_ori) glht(result, linfct = mcp(f_GROUP="Tukey") ) Error in `[.data.frame`(mf,...

Quick question about the usage of glht. I'm working with a data set from an experiment where the response is bounded at 0 whose variance increases with the mean, and is continuous. A Gamma error distribution with a log link seemed like the logical choice, and so I've modeled it as such. However, when I use glht to lo...

...data is over dispersed so I have fitted a negative binomial glm (glm.nb) and simplified using stepAIC from the MASS package etc. There are significant differences in the number of insects attracted to the different chemical (semio) and to the two different CO2 (release rates) I have then used the glht function from the multcomp package to do multiple comparisons to see what the specific differences between the levels are for semio and CO2 using the code below which works great but what I would like to do is to do comparisons combining the factors e.g a comparison for semioA at CO at level 1 vs S...

...789695.n4.nabble.com/How-set-lm-to-don-t-return-NA-in-summary-td3722587.html). If I use aov() instead of lm() I get no NA in model estimates and I use gmodels::estimable() without problems. Ok! Now I'm performing a lot of contrasts and I need correcting for multiplicity. So, I can use multcomp::glht() for this. However, glht() return an error message that is not compatible with my expectations. Someone know I or has a suggestion for? Below some reproducible code. # toy data adi <- expand.grid(cult=gl(1,3,la=LETTERS[1]), fert=101) fat <- expand.grid(cult=gl(2,3,la=LETTERS[2:3]), fert=seq...

...", "ma", "ra", "lp", "mp", "rp"), 3 ) ) library(car) model.Anova <- Anova( lm(eeg ~ 1), idata=data.frame(Condition, Region), idesign=~Condition*Region ) ) I'm now trying to do post-hoc comparisons between all levels of Condition using glht() from the multcomp package. I do this using the way that has worked for me with lmer() objects in the past: set up a contrast matrix and then feed it to glht(): designmatrix <- matrix(0, nrow=3, ncol=18) rownames(designmatrix) <- c("Cond1_minus_Cond2", "Cond3_minus_Cond1&quot...

Hi folks, I am working with repeated measures data and I ran into issues where the paired t-test results did not match those obtained by employing glht() contrasts on a lme model. While the lme model itself appears to be fine, there seems to be some discrepancy with using glht() on the lme model (unless I am missing something here). I was wondering if someone could help identify the issue. On my actual dataset the differences between glht() and...

...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 *** edadysexo:log(lcc) 2 0.063 0.0317 1.6021 0.2025 Residuals 509 10.085 0.0198 Then, I tried to do a post-hoc using glht from multcomp package, but, because the interaction it's not siginificant i did it just for the factor > summary(glht(ancova, linfct=mcp(edadysexo="Tukey"))) Simultaneous Tests for General Linear Hypotheses Multiple Comparisons of Means: Tukey Contrasts Fit: aov(for...

...;-subset(MyData,Attribute=="ChromaL") tapply(data$value, list(Product=data$Product), mean, na.rm=TRUE) model <- lme(value ~ Product+Time+Arm+Product*Arm+Product*Time+Product*Arm*Time, random = ~1 | Subj,data =data) summary(model) x<-anova(model) x library(multcomp) su<-summary(glht(model,linfct=mcp(Product="Tukey"))) ##length(su) ##su[1:(length(su)-4)] x11() plot(summary(glht(model,linfct=mcp(Product="Tukey"))),cex.axis=0.6) ##For Each Product Comparison across All Time Points. data<-MyData data<-subset(data,Product=="a") tapply(data$valu...

...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 comparisons between factors i tried with glht of multcomp package by Torsten Hothorn I use "Tukey" contrast, but d?dn't get diferencies > summary(glht(mcrm3,linfct=mcp(month="Tukey"))) Estimate Std. Error z value Pr(>|z|) may - april == 0 -18.2470 1555.0564 -0.012 1.0000 june - april...

I have a question about TukeyHSD and the glht function because I'm getting different answers when a covariate is included in model for ANCOVA.? I'm using the cabbages dataset in the 'MASS' package for repeatability.? If I include HeadWt as a covariate, then I get different answers when performing multiple comparisons using...

Hi R helpers! I have used a glht as a post-hoc test on an lmer with: -2 treatments (A & B) -1 categorical explanatory variable (song type) -1 response variable (latency to respond) I wanted to make comparisons between the categorical variables depending on treatment. At the moment the glht simply returns comparisons of each...

...data set I've been attempting to analyze using the lme function in the nlme package. Repeated searches here and other places lead me to believe I have specified my model correctly. However, I am having trouble with post-hoc tests. From what I gather, other people are successfully using the glht function from the multcomp package to perform post-hoc tests. I've tried multiple iterations, but can't seem to get it to work. Here is (a subset of) what I have been trying. Any help would be greatly appreciated: > model.3<-lme(fixed=Totnum~Wk*Pop, random=~1|nUID, data=nona) #Wk...

Hi, I use glht to make multcomp, using Tukey, from a glm model. It is possible to get a more simplified output of result? Somethink like ordering by letters. Thanks Ronaldo -- Human kind cannot bear very much reality. -- T. S. Eliot, "Four Quartets: Burnt Norton" -- > Prof. Ronaldo Reis J?nior...