similar to: export glht to LaTeX

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

Hello, I am trying to determine the most appropriate way to run post-hoc 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:

Dear all, I am trying to export my fixed effect results to Latex. I am using the plm package with the summary function. However, it does not look like apsrtable, stargazer, or any other package can accompany using the plm package. I am interested in a classic table with the coefficient in one row followed by the standard error in paranthesis in the next row and stars by the coefficient to show

Hi All, I am trying use 'multcomp' for multiple comparisons after my ANOVA analysis. I have used the following code to do ANOVA: dat <- matrix(rnorm(45), nrow=5, ncol=9) f <- gl(3,3,9, label=c("C", "Tl", "T2")) aof <- function(x) { m <- data.frame(f, x); aov(x ~ f, m) } amod <- apply(dat,1,aof) Now, how can I use

Dear *, I would like to obtain for each factor of my anova model the "response variable vs factor" plot with means and 95% Tukey HSD intervals. I would appreciate any information on how to do that. Cheers -------------------------------------------------------------------- Max MANFRIN Tel.: +32 (0)2 650 3168 IRIDIA - CoDE, CP 194/6

Hello, I'm a totally newbie to R and I'm taking a class using S+. In the class we use the multcomp command which takes a aov object and calculates confidence intervals for all pairwise differences by the Fisher least significant differences method. How can I do this in R. Thank you for taking the time with such a basic question. I've been looking on the net for a few days and I

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

I used the multcomp package sometime back for doing multiple comparisons. I see that it has been updated and the methods like simint are no longer supported. When I run the program it prompts to me to use glht. How do I get the lower and upper conf int and the pValues using glht? Does anyone have an example? Thanks ../Murli [[alternative HTML version deleted]]

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

Dear all, glht (from the multcomp package) needs a term and a model component in it's fitted model. In fitted models from e.g. repeated measurements ANOVAs I do not find neither model nor term. Is it possible to build together a model and term component myself, so that glht will work for repeated measurements ANOVAs? If so, how would I do that? Best regards, Michael Zehetleitner

Hi All, I have performed a 3-way ANOVA analysis for my experimental data using aov function. My simple R funtion for this is: 3aof <- function(x){ m <- data.frame(R,S,T, x); anova(aov(x ~ R+S+T+R*S+R*T+S*T+R*S*T, m) ) } Now, I am getting P values for all the main and interactions effects. If I want to perform postdoc test on one of my main effects, say T, what method I should use (i have

Hi All, Another nls related problem (for background, I'm migrating a complicated modelling package from S-plus to R). Below I've reduced this to the minimum necessary to demonstrate my problem (I think); the real situation is more complicated. Two similar selfStart functions, ssA and ssB. The 'initial' function for ssB modifies its arguments a little and then calls getInital

Dear listers, I am trying to export my regression table to my latex document. Let's say I have two variables: an ordered factor: group <- gl(3,5,20, labels=c("Ctl","Trt","prp")) and a continuous variable: weight <- runif(20) I want to regress group over weigth, therefore I run: reg2 <- polr(group ~ weight, Hess = TRUE, method = "logistic",

Hi everyone, I am fairly new to R, and I am aware that others have had this problem before, but I have failed to solve the problem from previous replies I found in the archives. As this is such a standard procedure in psychological science, there must be an elegant solution to this...I think. I would much appreciate a solution that even I could understand... ;-) Now, I want to calculate a

Dear R-listers, I am a newbie with R and I am struggling with something I consider very basic. I wish to produce a table (to import in a latex file) of summary statistics, but for as much as I've been looking around and trying various alternatives (plyr, reporttools, pastecs and Hmisc) I haven't found what I am looking for. Probably I am doing something wrong, but I can't figure out

Hi, I am trying to setup a Driver Domain for a NIC. I use ubuntu Jaunty Dom0 and the same kernel for the Driver Domain as well. I have successfully pass-through-ed the PCI device to the DomU ( Driver Domain). But i am not sure as to what i will have to do next to get the IDD functional ? -- -- With Regards , Amod Jaltade Good, Fast, Cheap: Pick any two (you can''t have all

I'd like to take a different approach to the old question of dataset variable labels. Support for their use in output is low. For example, among packages that provide tables of model estimates only 'stargazer' provides support for these labels (apologies if I missed support from aprstable, memisc, texreg, xtable). Part of the lack of support could be that variable labels are not

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) z p treatmentpyridoxine -0.063 0.939 0.161

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/type, data=dat) glht(dat.lme, linfct = mcp(type

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, nhypo[checknm]) : undefined columns selected I can't