similar to: Difficulties Using glht.mmc to Calculate Tukey Intervals for Means

Displaying 20 results from an estimated 6000 matches similar to: "Difficulties Using glht.mmc to Calculate Tukey Intervals for Means"

2011 Aug 06
1
multcomp::glht() doesn't work for an incomplete factorial using aov()?
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.
2008 May 28
2
Tukey HSD (or other post hoc tests) following repeated measures ANOVA
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
2012 Jan 02
1
Is using glht with "Tukey" for lme post-hoc comparisons an appropriate substitute to TukeyHSD?
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:
2011 Mar 04
2
glht: Problem with symbolic contrast for factors with number-levels
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)),
2013 Jan 14
1
Tukey HSD plot with lines indicating (non-)significance
Dear list members, I'm running some tests looking at differences between means for various levels of a factor, using Tukey's HSD method. I would like to plot the data as boxplots or dotplots, with horizontal significance lines indicating which groups are statistically significantly different, according to Tukey HSD. Here's a nice image showing an example of such a graphical
2011 Mar 01
1
glht() used with coxph()
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
2008 Jan 10
1
general linear hypothesis glht() to work with lme()
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
2013 Jul 25
1
lme (weights) and glht
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 --> works fine
2012 Dec 05
1
Using multcomp::glht() with Anova object
Hello everyone, I've conducted a Type III repeated-measures ANOVA using Anova() from the car package, based on the suggestions at http://blog.gribblelab.org/2009/03/09/repeated-measures-anova-using-r/(option 3) and http://languagescience.umd.edu/wiki/EEG#ERP_ANOVA_in_R. My ANOVA has two factors: Condition (3 levels) and Region (6 levels) and their interaction. Below is code to run the Anova
2008 Jan 11
1
glht() and contrast() comparison
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), sometimes both glht() and contrast() worked and gave nearly the same p values;
2010 Jul 21
1
post hoc test for lme using glht ?
Hi, I have a fairly simple repeated measures-type 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
2009 Mar 22
1
Multiple Comparisons for (multicomp - glht) for glm negative binomial (glm.nb)
Hi I have some experimental data where I have counts of the number of insects collected to different trap types rotated through 5 different location (variable -location), 4 different chemical attractants [A, B, C, D] were applied to the traps (variable - semio) and all were trialled at two different CO2 release rates [1, 2] (variable CO2) I also have a selection of continuous variables
2011 Jul 26
3
a question about glht function
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
2008 Apr 15
2
glht with a glm using a Gamma distribution
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 look for differences between groups, I get significant
2012 Mar 28
1
discrepancy between paired t test and glht on lme models
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
2012 Feb 06
2
glht (multicomparisons) with a binomial response variable
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
2012 Jan 13
1
GLHT in multcomp: Two similar models, one doesn't work
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
2007 Nov 21
1
multiple comparison (glht) problem
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
2013 Feb 26
1
Getting the correct factor level as Dunnett control in glht()
Hello all, I would like to do a Dunnett test in glht(). However, the factor level I want to use as the control is not the first. dunn1<-glht(model3, linfct = mcp(Container = "Dunnett"), alternative = "less") The factor container has 8 levels, so it would be nice not to manually enter in all of the contrasts. I originally discovered glht() when working with a glm model
2012 Nov 07
1
A warning message in glht
Dear all, I was wondering if you could give me any suggestions/help on the following issue. So I carried out the analysis of my data using generalized linear model (glm). After that, to check for multiple comparisons, I applied the glht function from the multcomp package in R. The output, however, gave me a warning (please see below). So my question is whether this warning is smth that I should