similar to: Using multcomp::glht() with Anova object

Hello everyone, Does anyone know what would cause the skewness() function (from e1071), as well as skew() from psych, to return a value of NaN? I have a vector of positively-skewed data (https://docs.google.com/file/d/0B6-m45Jvl3ZmYzlHRVRHRURzbVk/edit?usp=sharing) which these functions return a value for like normal: > skewness( data ) # returns 1.400405 but when I instead give those

Hello, duplicated() does not seem to work for a long vector. For example, if you download the data from https://docs.google.com/open?id=0B6-m45Jvl3ZmNmpaSlJWMXo5bmc (a vector with about 12,000 numbers) and then run the following code which does duplicated() over the whole vector but just shows the last 30 elements: data.frame( tail(verylong, 30), tail(duplicated(verylong), 30) ) you'll see

i ran this model > model2<-glm(rojos~ageandsex+sector+season+sector:season,quasipoisson) > glht(model2,linfct=mcp(ageandsex="Tukey")) General Linear Hypotheses Multiple Comparisons of Means: Tukey Contrasts Linear Hypotheses: Estimate M - H == 0 0.2898 SUB - H == 0 -0.2261 SUB - M == 0 -0.5159 I tried to do the same changing factor season

Hello, I have a list of data with multiple elements, and each element in the list has multiple variables in it. Here's an example: ### Make the fake data dv <- c(1,3,4,2,2,3,2,5,6,3,4,4,3,5,6) subject <- factor(c("s1","s1","s1","s2","s2","s2","s3","s3","s3",

To whom it may concern: The help page for ?legend refers to a `title.cex` parameter, which suggests that the function has such a parameter. As far as I can tell, though, it doesn't; here's an example: > plot(1,1) > legend("topright",pch=1, legend="something", title="my legend", title.cex=2) Error in legend("topright", pch = 1, legend =

Right, that's my point. The help page mentions a `title.cex`, like I said; saying that `cex` sets the default `title.cex` sure implies to me (and presumably to the other people whose discussion I linked) that a `title.cex` parameter exists. Since no such parameter exists, this bit in the documentation is misleading (suggesting that there is a `title.cex` parameter which can be set, when there

Hello everyone, I am running a mixed effects model where I have two fixed factors, one with 2 levels and one with 4, and their interaction. Let's say these are my factors and their levels: FirstFactor: 1, 2 SecondFactor: A, B, C, D For the interaction, I am interested in the four two-way comparisons, not the two four-way comparisons. In other words, I want to test whether 1A is

Hello everyone, I am testing a model in which I have a two-level factor (let's call it First [1, 2]) nested under a four-level factor (let's call it Second [A, B, C, D]). I have used the following model to get coefficients representing whether, for each level of Second, there is a significant difference (in the outcome variable, Latency) between the levels of First: test <- lmer(

Hi all, I've posted this question before, but did not get any reply. I post it again here and see if anybody can help. Thank you. I have a nested model with the following effects fixed: treatments random: experiment_date I used lme() to model the data mod1 <- lme(N_cells ~treatments-1, random=~1|experiment_date, method='ML') Then I want to compare all the other

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

It's been a few weeks I'm racking my brains on how to use the function glht the package multcomp to test interactions. Unfortunately, the creator of the package forgot to put a sample in pdf package how to do it. I have looked in several places, but found nothing. If someone for the love of God can help me I'll be extremely grateful. The model is glm. -- View this message in context:

fixed @ R-forge. New version should appear on CRAN soon. Thanks for the report! Torsten > > ---------- Forwarded message ---------- > Date: Sat, 3 Sep 2011 23:56:35 +0200 > From: Ulrich Halekoh <Ulrich.Halekoh at agrsci.dk> > To: "r-help at r-project.org" <r-help at r-project.org> > Subject: [R] glht (multcomp): NA's for confidence intervals using

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

I am not sure whether there is a bug. When I tested the example given for "glht" in the help, I entered the following error: Running commands: amod <- aov(minutes ~ blanket, data = recovery) rht <- glht(amod, linfct = mcp(blanket = "Dunnett"), alternative = "less") Errors are: Error in try(coef.(model)) : could not find function

Dear List, Could you tell why I get the error message? > library(multcomp) > data("cholesterol") > m = aov(response ~ trt, data = cholesterol) > cht <- glht(m, linfct = mcp(trt = "Tukey")) Error: could not find function "glht" Thank you G?bor

Hej, Calculation of confidence intervals for means based on a model fitted with lmer using the package multcomp - yields results for calpha=adjusted_calpha - NA's for calpha=univariate_calpha Example: library(lme4) library(multcomp) ### Generate data set.seed(8) d<-expand.grid(treat=1:2,block=1:3) e<-rnorm(3) names(e)<-1:3 d$y<-rnorm(nrow(d)) + e[d$block]

Hello R users, I'm analyzing an experiment in a balanced incomplet block design (BIB). The effect of blocks are assumed to be random, so I'm using nlme::lme for this. I'm analysing another more complex experiments and I notice some diferences from doBy::popMeans() compared multcomp::glht() and contrast::contrast(). In my example, glht() and contrast() were equal I suspect popMeans()

Hello, I have a question as to how the syntax for glht(package multcomp) and estimable (gmodels) works, since I'm not getting everything from the documents I've googled so far, especially with models with 2nd order terms. A modestly complex model: 2-way anova with one continuous covariate, no random effects(and no repeated measures) to keep it modestly complex: Y = treatmentgroup + sex

Hi R users, I sent a message yesterday about NA in model estimates ( http://r.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.

Dear all, I studied in tank prey fish behavior. Using the design described below (and R code), I want to test the effects of both habitat and predator (and interaction) on prey fish's vertical distribution, which was recorded (with repeated measures) as a categorical variable. I found that package mlogit might fit to my need but I don't know how to specify my complex design in the