Displaying 20 results from an estimated 800 matches similar to: "R: Error with glht function: Error in mcp2matrix(model, linfct = linfct) : Variable(s) 'Type' have been specified in 'linfct' but cannot be found in 'model'!"
2012 Jun 22
0
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)
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
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
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
2010 Nov 17
1
lme weights glht
Dear R-user
I used lme to fit a linear mixed model inlcuding weights=varPower().
Additionally I wanted to use glht to calculate Tukey-Kramer multiple
comparision.
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))?
>
2007 Aug 28
0
Problem with lme using glht for multiple comparisons
Hi everyone,
I am new to R and have a question that relates to unplanned post-hoc comparisons using the multcomp package after a mixed effects model. I couldn't find the answer to it in the archive or in any manual.
I have a dataset in which several plants have been treated in a particular way and a continuous response variable has been measured depending on several leaves per plant. I am
2012 Jan 11
2
problems with glht for ancova
I've run an ancova, edadysexo is a factor with 3 levels,and log(lcc) is the
covariate (continous variable)
I get this results
> ancova<-aov(log(peso)~edadysexo*log(lcc))
> summary(ancova)
Df Sum Sq Mean Sq 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 ***
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
2007 Nov 07
1
bug in multcomp?
I am running a linear model with achiev as the outcome and major as my
iv (5 levels). The lm statement runs fine, but for the glht command 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 =
2012 Jun 13
1
Tukey Kramer with ANOVA (glm)
Hello,
I am performing a BACI analysis with ANOVA using the following glm:
fit1<-glm(log(Cucs_m+1)~(BA*Otter)+BA+Otter+ID+Primary, data=b1)
The summary(aov(fit1)) shows significance in the interaction; however, now I
would like to determine what combinations of BA and Otter are significantly
different (each factor has two levels). ID and PRIMARY substrates are
categorical and included in
2011 Jul 16
1
Creating composite factor and changing format from character to factor
Dear Help-list, I have a dataframe containing 6 variables, 4 of which are factors, 2 numeric. I want to create another factor variable (SitePos) by combining 2 existing factors (Site and Position). I have tried a number of approaches based on trolling the R FAQs, various R webpages, etc., none of which work. One approach e.g. Data1$SitePos <- paste(Data1$Site, Data1$Position) creates the
2010 Aug 30
1
Help With Post-hoc Testing
I am trying to do post-hoc tests associated with a repeated measures
analysis with on factor nested within respondents.
The factor (SOI) has 17 levels. The overall testing is working fine, but I
can''t seem to get the multiple comparisons to work.
The first step is to "stack" the data.
Then I used "lme" to specify and test the overall model.
Finally
2008 Oct 31
0
help with contrasts for a binomial 3-way GLM
Hi
I am a new user the R and I am very grateful for all your help but.......
I have a problem and I can't resolve yet. I am trying to get the contrasts for a binomial 3-way GLM (T= 4 temperature, t= 2 time and c= 2 substrate levels, plus treatment control) in total they are 17 treatments.
I have tried with the glht but this function only work for 1-way GLM,
acacia<-cbind(g,N-g)
2010 Mar 15
1
Multiple comparisons for a two-factor ANCOVA
I'm trying to do an ANCOVA with two factors (clipping treatment with two
levels, and plot with 4 levels) and a covariate (stem diameter). The
response variable is fruit number. The minimal adequate model looks like
this:
model3<-lm(fruit~clip + plot + st.dia + clip:plot)
I'd like to get some multiple comparisons like the ones from TukeyHSD, but
TukeyHSD doesn't work with the
2012 Feb 12
2
ANCOVA post-hoc test
Could you please help me on the following ANCOVA issue?
This is a part of my dataset:
sampling dist h
1 wi 200 0.8687212
2 wi 200 0.8812909
3 wi 200 0.8267464
4 wi 0 0.8554508
5 wi 0 0.9506721
6 wi 0 0.8112781
7 wi 400 0.8687212
8 wi 400 0.8414646
9 wi 400 0.7601675
10 wi 900 0.6577048
11 wi 900
2012 Jan 12
0
glht (multicomparisons) with an interaction factor
Hi,
i was working with this model
> mq<-glm(rojos~edadysexo*zona*estacion,quasipoisson)
and i get this minimal adequate model
> anova(mq5,test="F")
Df Deviance Resid. Df Resid. Dev F Pr(>F)
NULL 518 64799
edadysexo 2 1556.5 516 63243 8.9434 0.0001524 ***
zona 4
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
2012 Aug 03
0
MANOVA with repeated measures in R
Dear list member,
I deperately need an help in performing a MANOVA in R, but I encountered some
problems both in the design and in the synthax with R.
I conducted a listening experiment in which 16 participants had to rate the audio
stimuli along 5 scales representing an emotion (sad, tender, neutral, happy and aggressive).
Each audio stimulus was synthesized in order to represent a
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)),
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.
2011 Sep 05
0
glht (multcomp): NA's for confidence intervals using univariate_calpha (fwd)
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