search for: mcp2matrix

Hello everybody, problem solved, there was a typo. I wrote Type instead of Material Best ----Messaggio originale---- Da: angelo.arcadi@virgilio.it Data: 22-giu-2012 11.05 A: <r-help@r-project.org> Ogg: Error with glht function: Error in mcp2matrix(model, linfct = linfct) : Variable(s) 'Type' have been specified in 'linfct' but cannot be found in 'model'! Dear list members, I get the following error when using the glht function to perform a post hoc analysis for an ANOVA with repeated measures: require(nlme) lm...

...st hoc analysis for an ANOVA with repeated measures: require(nlme) lme_H2H_musicians = lme(H2H ~ Emotion*Material, data=musicians, random = ~1|Subject) require(multcomp) summary(glht(lme_H2H_musicians, linfct=mcp(Type = "Tukey")), test = adjusted(type = "bonferroni")) Error in mcp2matrix(model, linfct = linfct) : Variable(s) 'Type' have been specified in 'linfct' but cannot be found in 'model'! I don´t understand why I get this error, but at the same time I am not an expert at all of R. I can give you some details more about the experimental design I...

...y data. I am *unclear how to code it to work with the interaction*; however, even when I attempt to use it only for a single factor, it does not work (see below). x<-aov(glm(Cucs_m~as.factor(BA),data=cuc)) glht(x, linfct=mcp(BA="Tukey")) .................................... Error in mcp2matrix(model, linfct = linfct) : Variable(s) ?BA? have been specified in ?linfct? but cannot be found in ?model?! Can anyone off suggestions on potential problems with my approach and/or script issues? Thank you very much in advance. -- View this message in context: http://r.789695.n4.nabble.com/Tuk...

...nd I get the following error. I noted that someone else asked the same question a while back but received no reply. I am hoping someone might know what is happening. anovaf2<-lm(achiev ~ major, data=data_mcp) > pairwise<- glht(anovaf2,linfct = mcp(major = "tukey")) Error in mcp2matrix(model, linfct = linfct) : Factor(s) major have been specified in 'linfct' but cannot be found in 'model'! Any help would be much appreciated. Rob. -- Robert A. Cribbie, PhD Department of Psychology York University Toronto, ON M3J 1P3 Phone: 416-736-2100 x88615 Emai...

...itePos + (1 | Eel), data = Data1) . The next step of a multiple comparison test on the output of the linear model: Model.G.mct = glht(Model.G, linfct = mcp(SitePos = "Tukey")) fails because the mct does not recognize "SitePos" as a factor and gives error message: "Error in mcp2matrix (model, linfct = linfct): Variable(s) 'SitePos' of class 'character' is/are not contained as a factor in 'model'. My final step is outputting the mct results: summary (Model.G.mct, test = adjusted(type = "single-step")). Any suggestions as to how to create a com...

...(model.3) numDF denDF F-value p-value (Intercept) 1 592 649.7753 <.0001 Week 5 592 302.9706 <.0001 Pop 1 222 70.7268 <.0001 Week:Pop 5 592 36.8576 <.0001 > summary(glht(model.3, linfct=mcp(Wk = "Tukey"))) Error in mcp2matrix(model, linfct = linfct) : Variable(s) ?Wk? of class ?integer? is/are not contained as a factor in ?model?. > is.factor(Wk) [1] FALSE > Week<-factor(Wk) > is.factor(Week) [1] TRUE > model.3<-lme(fixed=Totnum~Week*Pop, random=~1|nUID) > summary(glht(model.3, linfct=mcp(Week =...

...olution, data = stack) > anova(Lmes.mod) numDF denDF F-value p-value (Intercept) 1 2383 2894.8342 <.0001 solution 1 2383 0.0003 0.9870 iobs 1 147 0.0126 0.9109 > summary(glht(Lmes.mod, linfct=mcp(solution="Tukey"))) Error in mcp2matrix(model, linfct = linfct) : Variable(s) ''solution'' of class ''numeric'' is/are not contained as a factor in ''model''. > I don''t understand the error since "solution" is clearly a factor in the model. Any suggestions woul...

...== 0 -0.9055 0.3573 -2.534 0.0302 * O - A == 0 -2.5638 0.3917 -6.545 <0.001 *** O - In == 0 -1.6584 0.3766 -4.404 <0.001 *** --- Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1 (Adjusted p values reported -- single-step method) *Warning message: In mcp2matrix(model, linfct = linfct) : covariate interactions found -- default contrast might be inappropriate* -- View this message in context: http://r.789695.n4.nabble.com/A-warning-message-in-glht-tp4648770.html Sent from the R help mailing list archive at Nabble.com.

...0.04562 -0.491 0.961 wi - au == 0 0.01203 0.04562 0.264 0.994 su - sp == 0 -0.08934 0.04562 -1.958 0.204 wi - sp == 0 -0.05493 0.04562 -1.204 0.624 wi - su == 0 0.03441 0.04562 0.754 0.875 (Adjusted p values reported -- single-step method) Warning message: In mcp2matrix(model, linfct = linfct) : covariate interactions found -- default contrast might be inappropriate My questions are: - Did I make a mistake somewhere? (I probably did!) - Could I do pairwise ANCOVAs and thus have just two factor levels (=two regression slopes) to compare each time? What does t...

...data=ME, random=~1|Plot/SubPlot, weights=varPower(form=~Diversity), na.action=na.omit, subset=ME$Species=="Ace_pse", method="ML") summary(H08_lme) anova(H08_lme) ME$Diversity=factor(ME$Diversity) g_H08_lme<-glht(H08_lme, linfct=mcp(Diversity="Tukey")) Error in mcp2matrix(model, linfct = linfct) : Variable(s) ‘Diversity’ have been specified in ‘linfct’ but cannot be found in ‘model’! [[alternative HTML version deleted]]

...t-hoc analysis (multiple comparisons) for the fixed factor EFN. I tried the following code. According to the documentation this should work: > > Post <- glht(LM, linfct = mcp(Leafage = "Tukey")) > However, I get this error message and don't know what to do: Error in mcp2matrix(model, linfct = linfct) : Factor(s) Leafage have been specified in ?linfct? but cannot be found in ?model?! The factor is specified, right? So what is the problem? If I do the same with an normal Anova (command: aov), it works. What is the problem with the lme command? Thank you very much in a...

...ons don't work Ø acacia3<-glm(acacia~T*t*c,binomial) Ø > glht(acacia3, linfct = mcp(T = "Tukey")) Ø Error in modelparm.default(model, ...) : Ø dimensions of coefficients and covariance matrix don't match Ø Warning message: Ø In mcp2matrix(model, linfct = linfct) : Ø covariate interactions found -- default contrast might be inappropriate Other function could be simtes but this was deprecated from package multcomp There are others options to get comparisons contrasts for model GLM with interactions? or this test do...

...on. error: > glht(modelF, linfct=mcp(Species="Tukey")) Error in glht.matrix(model = list(modelStruct = list(reStruct = list(SubPlot = -0.305856275920955, : ?ncol(linfct)? is not equal to ?length(coef(model))? > glht(modelF, linfct=mcp(Diversity="Tukey")) Error in mcp2matrix(model, linfct = linfct) : Variable(s) ?Diversity? of class ?integer? is/are not contained as a factor in ?model?. Does anyone know, if glht does not function using weights/interactions in lme? Thanks Sibylle LME MODEL > Kaltenborn<-read.table("Kaltenborn_YEARS.txt",...

...arisons of Means: Tukey Contrasts Linear Hypotheses: Estimate 151Nat - 151Trans == 0 -1.924 HC - 151Trans == 0 -7.942 HE - 151Trans == 0 -4.637 HC - 151Nat == 0 -6.018 HE - 151Nat == 0 -2.712 HE - HC == 0 3.305 Warning message: In mcp2matrix(model, linfct = linfct) : covariate interactions found -- default contrast might be inappropriate How can I get it to give me the same sort of output that TukeyHSD gives with just a regular two-way ANOVA? Thanks for your help -Eric Scott [[alternative HTML version deleted]]

...ar Hypotheses: Estimate Std. Error t value Pr(>|t|) M - H == 0 -1.8218 1.1111 -1.640 0.230 SUB - H == 0 -0.9298 1.1957 -0.778 0.717 SUB - M == 0 0.8921 1.1130 0.801 0.702 (Adjusted p values reported -- single-step method) Mensajes de aviso perdidos In mcp2matrix(model, linfct = linfct) : covariate interactions found -- default contrast might be inappropriate Two question: 1) Why I don't get differences in edadysexo when i got it in the ancova 2) About the warning message. Why R said "covariate interactions found" of i didn't get it in...