Please post to R-help:
Hi all -
I wanted to share a message putting TWO upcoming awards on your radar. These
are jointly sponsored by the Graphics and Computing sections of the American
Statistical Association (ASA):
The student Paper Award. Full details here:
https://community.amstat.org/j
All -
I run an automated script that pulls in some market data, makes some charts,
and posts them to twitter. A couple of them per day, and then once per month
there's a little flurry around the CPI report.
For a while rtweet() worked great. Then v2 happened and Oauth2.0. The package
broke, wa
Dear All:
Re: Post-hoc pairwise Fisher’s exact tests with confidence Intervals
I am trying to conduct a Post-hoc pairwise comparison for comparing the
proportions of the ones in the 7 groups using the fisher exact test. I have
a data with 7 variables, data = (0,1). Event = 1.
*Q1.* Is ther
Hi,
I am interested in running sensitivity analysis (variance-based). But
instead of running Monte Carlo simulations in R, I already have my sample
data in two tables.
So how do I run Sobol on my own data then? Does that mean that the model =
null? And then to use tell()? I cannot find any exampl
> Thomas Subia
Could you please explain the difference between:
> any differences in variance between factors.
and
> variance differences between factors
?
***
This email and any attachments are confidential. Any use...{{drop
1. Wrong list. This list is about R programming, not statistical questions
(though they do sometimes intersect). stats.stackexchange.com might be a
better place for you to post your question.
2. Try a search on "post hoc test of variances" at rseek.org. You might
find something relevant.
3. What
Colleagues,
When using Levene's test, I can identify if there are any differences in
variance between factors. This is straight forward
Is there a way to do a post hoc test to identify variance differences between
factors? This is not so straight forward.
All the best
Thomas Subia
[[al
ang ; r-help mailing list
Subject: Re: [R] Post for R
Hi Carrie,
You may have a problem with this if some subsets are empty:
L3<-lapply(split(df,cut(df$max,seq(0,1,by=0.01))),
split,cut(df$submax,seq(0,0.2,by=0.02)))
Jim
On Thu, Jun 1, 2017 at 12:48 PM, carrie wang via R-help
wrote:
>
Hi Carrie,
You may have a problem with this if some subsets are empty:
L3<-lapply(split(df,cut(df$max,seq(0,1,by=0.01))),
split,cut(df$submax,seq(0,0.2,by=0.02)))
Jim
On Thu, Jun 1, 2017 at 12:48 PM, carrie wang via R-help
wrote:
>
> Hello,
> I want to split the dataframe into 1000 groups base
Carrie,
I would suggest a few things before posting your code here:
- Put a dput(df)
- Format it properly, as it stands it won't compile, because you're missing
newlines/semicolons between, e.g. Z <- list()*; *G <- list(); for (i in
length(L1)){ Z=data.frame(L1[i])*;* G <- split(Z$submax,"0.02")*;
Hello,
I want to split the dataframe into 1000 groups based on two column values(max
value and second max value). First, I made two lists L1 and L2. L1 is the list
divided into 100 groups based on the range of max value and L2 is divided into
10 groups based on the second max values. Now I wa
Dear Katherina,
Multcomp can't handle interactions automatically. You need to create the
contrasts manually.
Best regards,
Thierry
Op 25-mrt.-2017 08:13 schreef "Katharina Voigt" :
> Hi,
> I want to obtain post hoc comparisons for a model with a three-way
> interaction (FullModel5 <- lmer(CIVA
Hi,
I want to obtain post hoc comparisons for a model with a three-way interaction
(FullModel5 <- lmer(CIVADmc ~ 1 + Factor1 * Factor2 * Factor3 + (1|ID) + (1 |
Item), data=Exp3_WTP_diffi).
I tried: "summary(glht(FullModel4, linfct = mcp(Factor1*Factor2*Factor3 =
"Tukey")), test = adjusted("holm
You made it. Next time set your email program to send plain text instead of
HTML format to avoid us receiving a corrupted version of what you sent. (This
is a plain text mailing list. )
You don't need looping, you need ?merge and ?ifelse.
Df1 <- merge( Df1, Df2, all.x = TRUE, by = c ( "Date", "
Hello.
Im trying to post the following message in R-Help.
I think I must send it via email to do so, so here it is:
Hello,
I need help with some code.
Basically, I have experiments results which I need to process.
I have 2 dataframes with 3 columns
Df1 <- data.frame (Date, Celllin
> On Nov 5, 2015, at 6:34 AM, Luke Gaylor wrote:
>
> Hello there,
>
> I have registered for both through nabble and R-help-request with this email.
>
> I want to post the following question:
>
> I want to implement a Hosmer Lemeshow Goodness of Fit test to my survival
> analysis.
> In R we c
Hello there,
I have registered for both through nabble and R-help-request with this email.
I want to post the following question:
I want to implement a Hosmer Lemeshow Goodness of Fit test to my survival
analysis.
In R we can use the hoslem.test() function.
The x values are our observations, an
My name is Thalita, and I am a Phd student from Brasil.
I am trying to do a post hoc of ANCOVA to compare three slopes with Tukey test.
I am using:
#percentagem: dependent variable
#tratamento: factor
#tempo: covariate
#ANCOVA
ancova(percentagem~tratamento*tempo, data=data)
summary(ancova(pe
Hi Richard,
Thank you very much for your cooperation. I installed the packages "HH" and
run the following model:
Bud.aov<-aov(terms(Budburst~CO2*SoilTemp*Photoperiod+Greenhouse/(SoilTemp*Photoperiod),keep.order=TRUE),data=data)
> summary(Bud.aov)
Hi Richard,
Thank you very much for your cooperation. I installed the packages "HH" and
run the following model:
Bud.aov<-aov(terms(Budburst~CO2*SoilTemp*Photoperiod+Greenhouse/(SoilTemp*Photoperiod),keep.order=TRUE),data=data)
> summary(Bud.aov)
Yes, it is possible with the mmc function in the HH package.
install.packages("HH") ## if you don't have it yet.
library(HH)
?MMC
Look at the maiz example, the long last example in ?MMC.
When you are ready for followup questions, reply to this message to
R-help (not directly to me and
not to na
Dear R-help,
can you please post the following message to the r-nabble forum.
Thanks!
-
Dear R users,
I have been attempting to carry out post-hoc tests on a spli
] On
Behalf Of Reid, Doug (MNR)
Sent: Tuesday, July 29, 2014 2:57 PM
To: r-help@r-project.org
Subject: [R] Post hoc comparissons
Hi Folks,
I have been using the TukeyHSD to conduct post hoc comparisons. The challenge
is I have two interacting factors, one of which has 6 levels (cover types), and
Hi Folks,
I have been using the TukeyHSD to conduct post hoc comparisons. The challenge
is I have two interacting factors, one of which has 6 levels (cover types), and
the other 2 (study areas).As a result interpreting the post hoc comparisons
is difficult when you get a list of every poss
On 23/05/14 06:59, Claire wrote:
Thanks Bert,
Will post on r-sig-mixed-models list. Can't help it being in html
though as i sent the query via -email.
Huh? What do you mean by "-email"? Do you really mean "email" (without
the minus sign)? We *all* send our queries via email. This *is* emai
Thanks Bert,
Will post on r-sig-mixed-models list. Can't help it being in html though as i
sent the query via -email.
Cheers
Claire
> Date: Thu, 22 May 2014 09:29:44 -0700
> Subject: Re: [R] Post-hoc tests on linear mixed model give mixed results.
> From: gunter.ber...@gene.co
Wrong list! This does not concern R programming.
Post on the r-sig-mixed-models list instead in **PLAIN TEXT** rather than html.
Cheers,
Bert
Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374
"Data is not information. Information is not knowledge. And knowledge
is certainly not wis
Dear all,
I am quite new to R so apologies if I fail to ask properly. I have done a test
comparing bat species richness in five habitats as assessed by three methods. I
used a linear mixed model in lme4 and got habitat, method and the interaction
between the two as significant, with the random
Luigi,
agricolae has a nice function for this with the post hoc test as part of
the output.
AKK
On 10/21/2013 11:12 PM, arun wrote:
Hi,
Try:
pairw.kw(y,factor(x),conf=.95)
A.K.
On Monday, October 21, 2013 7:10 PM, luigi marongiu
wrote:
Dear all,
I am trying to apply a post hoc test t
Hi,
Try:
pairw.kw(y,factor(x),conf=.95)
A.K.
On Monday, October 21, 2013 7:10 PM, luigi marongiu
wrote:
Dear all,
I am trying to apply a post hoc test to a significant Kruskal-Wallis test.
I eventually found the function ‘pairw.kw()’ of the package “asbio”. This
function has the following s
Dear all,
I am trying to apply a post hoc test to a significant Kruskal-Wallis test.
I eventually found the function âpairw.kw()â of the package âasbioâ.
This
function has the following syntax:
pairw.kw(y, x, conf)
Arguments
y The response variable. A vector of quantitative responses.
Hello.
I am using the aovp() function from the library lmPerm with one factor
(group: 3 levels) controlling for 2 covariates. I now want to conduct a
post-hoc test using the same model. Unfortunately, I did not find an
appropriate test which works with 2 covariates. I would be grateful for any
sugg
Hi David,
Thank you very much for your reply. I do understand your point. I was requested
to do
power analyses for null findings by reviewers. I think simulations would be an
alternative
choice given the validity of post hoc power analysis is questionable. The
package, pamm
does simulation. But
Kota Hattori canterbury.ac.nz> writes:
> Dear all, I have been searching ways to run power analysis for
> mixed-effects models. However, I have not been successful in the
> research. Today I would like to ask your help. As long as I see from
> my search, Martin Julien wrote a package called pamm
On Jun 4, 2013, at 4:46 PM, Kota Hattori wrote:
Dear all,
I have been searching ways to run power analysis for mixed-effects
models. However, I have not been successful
in the research. Today I would like to ask your help. As long as I
see from my search, Martin Julien wrote a package
call
Dear all,
I have been searching ways to run power analysis for mixed-effects models.
However, I have not been successful
in the research. Today I would like to ask your help. As long as I see from my
search, Martin Julien wrote a package
called pamm for the power analysis. One of the limitations
On May 31, 2013, at 6:01 AM, Ulf Sandvik wrote:
> Hi,
>
> I have fitted a shared frailty model using coxph in the survival
> package with 'center' as random effect. Now I'm trying to obtain the
> conditional survival curve for a new test case that comes from one of
> the specified centers in the
Hi,
I have fitted a shared frailty model using coxph in the survival
package with 'center' as random effect. Now I'm trying to obtain the
conditional survival curve for a new test case that comes from one of
the specified centers in the model.
The data set on which the model is fitted contains 10
On May 14, 2013, at 21:04 , Bel Braz wrote:
> Hi R-people,
>
> I performed controlled experiments to evaluated the seeds germination of
> two palms under four levels of water treatments. I conducted a generalized
> linear model (GLM) with a Poisson distribution to verify whether there were
> sig
Hi R-people,
I performed controlled experiments to evaluated the seeds germination of
two palms under four levels of water treatments. I conducted a generalized
linear model (GLM) with a Poisson distribution to verify whether there were
significant differences in the number of seed germination (N
Dear all,
is it possible to run a post hoc comparison using the glht function on random
factors from a mixed model?
For example, in the model lie(Yield~1+Meadow, random=1|Site/Area/Quadrate).
thank you,
Vasillis Papathanasiou,
Marine SciencesPalaion Fokon 35-37Thessaloniki, 54454Greecetel:+30694
Hi everyone, I'm running the following analysis for two meadows and two
periods. I need to get the post hoc comparisons for the combination of the two
factors (meadowA*PeriodA, meadowA*PeriodB, meadowB*PeriodB, meadowB*PeriodA). I
use the function glht glht(model, linfct=mcp(Meadow="Tukey") in
Post-hoc test for a zero inflated continuous data set with a tweedie
distribution?
I have a zero inflated continuous data set of aphid feeding duration on 10+
species of plant. I have fitted a glm model with a tweedie distribution and
used anova() function to show that there is significance betwee
David,
How would you interpret the results of a post hoc test for sexcolor when
you have an interaction term with sexcolor in your model?
Perhaps it would be helpful to plot doy vs. predicted tle with confidence
intervals for each of the four levels of sexcolor at a fixed tl (e.g., the
mean).
Hi.
I'm analysing some fish biological traits with a gam in mgcv. After several
tries, I got this model
log(tle) = sexcolor + s(doy, bs = "cc", by = sexcolor) +log(tl)
sexcolor is a factor with 4 levels
doy is "day of year", which is modeled as a smoother
tl is "total length of the fish"
The sum
Amartya: This is probably more of a statistics question than an R question.
I would go with the Tukey HSD, were I you as that is its intention.
Is there anyone in your organization (school, company, etc) that does
statistical consulting? I have had wonderful experience working with the
consult
Please look at the ?mmc example for two-way ANOVA in library(HH).
If you don't already have HH you can get it with
install.packages("HH")
library(HH)
?mmc
mmc uses the glht function in the multcomp package for its calculations
and then draws the MMC graph.
Rich
On 10/19/12, Amartya wrote:
> Hi
Hi,
I was trying to figure out how to do post-hoc tests for Two Way ANOVAs and
found the following 2 approaches:
a. Do pairwise t-tests (bonferroni corrected) if one finds significance with
the ANOVA.
Link-
http://rtutorialseries.blogspot.com/2011/01/r-tutorial-series-two-way-anova-with.html
b.
On 16-Sep-2012 05:22:47 David Winsemius wrote:
>
> On Sep 15, 2012, at 7:17 PM, mcg wrote:
>
>> Dear moderator;
>>
>> I'm on the R-Mailing list with the same (giepe...@gmail.com) email address,
>> still I get the "Post by non-member..." message. Am I not a member than?
>
> It appears you are cu
On Sep 15, 2012, at 7:17 PM, mcg wrote:
> Dear moderator;
>
> I'm on the R-Mailing list with the same (giepe...@gmail.com) email address,
> still I get the "Post by non-member..." message. Am I not a member than?
It appears you are currently subscribed as one "6813 Non-digested Members".
--
Dear moderator;
I'm on the R-Mailing list with the same (giepe...@gmail.com) email
address, still I get the "Post by non-member..." message. Am I not a
member than?
Cheers,
Michael
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/li
On Sun, May 13, 2012 at 7:10 PM, Ruijie wrote:
> Hi all,
>
> I have data collected from a survey administered on a subset of the
> population. I also have the population proportions of variables such as
> gender, race and housing type. I would like to combine the weights from
> each separate cross
Hi all,
I have data collected from a survey administered on a subset of the
population. I also have the population proportions of variables such as
gender, race and housing type. I would like to combine the weights from
each separate cross tab (of gender, race and housing type) such that the
weigh
Thank you Richard and Frank for your very quick and helpful replies.
Cheers, Mark
On Thu, Feb 2, 2012 at 2:58 PM, Frank Harrell wrote:
> The R multcomp package provides one general approach to multiplicity
> correction. For general contrasts in lm and glm, the rms package's ols and
> Glm funct
The glht function in the multcomp package is what you are looking for.
There are additional examples in the ?MMC help file in the HH package.
Rich
On Thu, Feb 2, 2012 at 3:42 PM, Mark Na wrote:
> Hi R-helpers,
>
> TukeyHSD() works for models fitted with aov(), but could anyone point
> me to a f
The R multcomp package provides one general approach to multiplicity
correction. For general contrasts in lm and glm, the rms package's ols and
Glm functions make this even easier to use.
Frank
Mark Na wrote
>
> Hi R-helpers,
>
> TukeyHSD() works for models fitted with aov(), but could anyone p
Hi R-helpers,
TukeyHSD() works for models fitted with aov(), but could anyone point
me to a function that performs a similar post hoc test for models
fitted with lm() or glm()?
Thanks in advance,
Mark
__
R-help@r-project.org mailing list
https://stat.
On Feb 1, 2012, at 4:34 PM, Mark Na wrote:
Dear R-helpers,
I have an ANCOVA with a significant effect of the factor, which has
three levels. I wish to determine which of the levels are different
from each other but, because my model was fitted with lm(), I cannot
use TukeyHSD.
For some reason
Dear R-helpers,
I have an ANCOVA with a significant effect of the factor, which has
three levels. I wish to determine which of the levels are different
from each other but, because my model was fitted with lm(), I cannot
use TukeyHSD.
For some reason, I get different results (no significant effec
On 24.11.2011 04:34, M Subbiah wrote:
When I fit a logistic regression with 5 predictors (all of them are coded) i
get the standard error almost zero for the estimated coeffts. I request the
members to offer comments / suggestions / diagnostics?
[[alternative HTML version deleted]]
When I fit a logistic regression with 5 predictors (all of them are coded) i
get the standard error almost zero for the estimated coeffts. I request the
members to offer comments / suggestions / diagnostics?
[[alternative HTML version deleted]]
_
I have a mixed model with a binomial response, four factor variables and one
random factor.
m1=glmer(nbhf.hour~Season+Diel+Tidal.phase+Tidal.cycle+(1|POD.ID),family=binomial,data
=bl1,control=list(msVerbose=TRUE))
I have really need to try and find a post hoc test for this model and
finding the p
On 13.08.2011 06:52, bdeep...@ibab.ac.in wrote:
Hello,
I was trying to plot multiple graph using "par(mfrow=c(3,2))".
But this is giving me the following error:
Error in axis(side = side, at = at, labels = labels, ...) :
X11 font -adobe-helvetica-%s-%s-*-*-%d-*-*-*-*-*-*-*, face 1 at size
Hello,
I was trying to plot multiple graph using "par(mfrow=c(3,2))".
But this is giving me the following error:
Error in axis(side = side, at = at, labels = labels, ...) :
X11 font -adobe-helvetica-%s-%s-*-*-%d-*-*-*-*-*-*-*, face 1 at size 8
could not be loaded
Could someone decode this erro
you can mostly use data= arguments
on the individual functions.
Bill Venables.
-Original Message-
From: Venables, Bill (CMIS, Dutton Park)
Sent: Wednesday, 18 May 2011 9:07 AM
To: 'Bert Gunter'; 'Peter Ehlers'
Cc: 'R list'
Subject: RE: [R] Post-hoc tests in MASS
03 1.72e-01 1.50e-02 5.60e-06 ...
$ x2 : num 0.268811 0.034224 0.309802 0.060844 0.000315 ...
>
Bill Venables.
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Bert Gunter
Sent: Wednesday, 18 May 2011 12:08 AM
To: Peter Ehle
Folks:
> Only if the user hasn't yet been introduced to the with() function,
> which is linked to on the ?attach page.
>
> Note also this sentence from the ?attach page:
> " attach can lead to confusion."
>
> I can't remember the last time I needed attach().
>
> Peter Ehlers
Yes. But perhaps
On 2011-05-17 02:22, Timothy Bates wrote:
Dear Bryony: the suggestion was not to change the name of the data object, but
to explicitly tell glm.nb what dataset it should look in to find the variables
you mention in the formula.
so the salient difference is:
m1<- glm.nb(Cells ~ Cryogel*Day, da
011 03:21
To: Bryony Tolhurst; r-help@r-project.org
Subject: RE: [R] Post-hoc tests in MASS using glm.nb
?relevel
Also, you might want to fit the models as follows
Model1 <- glm.nb(Cells ~ Cryogel*Day, data = myData)
myData2 <- within(myData, Cryogel <- relevel(Cryogel, ref = "2"
h(data)
>
> But obviously I am still using the attach function, if not with 'data'!!
>
> Thanks again
>
> Bryony Tolhurst
>
> -Original Message-
> From: bill.venab...@csiro.au [mailto:bill.venab...@csiro.au]
> Sent: 17 May 2011 03:21
> To: Bryony Tolhurst
!!
Thanks again
Bryony Tolhurst
-Original Message-
From: bill.venab...@csiro.au [mailto:bill.venab...@csiro.au]
Sent: 17 May 2011 03:21
To: Bryony Tolhurst; r-help@r-project.org
Subject: RE: [R] Post-hoc tests in MASS using glm.nb
?relevel
Also, you might want to fit the models as foll
elp-boun...@r-project.org] On
Behalf Of bryony
Sent: Tuesday, 17 May 2011 3:46 AM
To: r-help@r-project.org
Subject: [R] Post-hoc tests in MASS using glm.nb
I am struggling to generate p values for comparisons of levels (post-hoc
tests) in a glm with a negative binomial distribution
I am try
I am struggling to generate p values for comparisons of levels (post-hoc
tests) in a glm with a negative binomial distribution
I am trying to compare cell counts on different days as grown on different
media (e.g. types of cryogel) so I have 2 explanatory variables (Day and
Cryogel), which are bot
David:
1. Sounds like you want to test the **interaction** of song type and treatment.
2. Does glht work ( S3 vs S4 class issues) with lmer fits?
3. If it works, does glht give sensible results? (see Doug Bates's
discussions on this issue).
4. Probably best to direct all such questions to the
Hi R helpers!
I have used a glht as a post-hoc test on an lmer with:
-2 treatments (A & B)
-1 categorical explanatory variable (song type)
-1 response variable (latency to respond)
I wanted to make comparisons between the categorical variables depending on
treatment.
At the moment the glht simp
Dear list,
I´m wondering if there is something analogous to the TukeyHSD function
that could be used for parametric terms in a GAM. I´m using the mgcv
package to fit models that have some continuous predictors (modeled as
smooth terms) and a single categorical predictor. I would like to do
post
Please read the maiz example in HH
install.packages("HH")
library(HH)
?MMC
Read all the way to the end of the maiz example.
On Sun, Jan 9, 2011 at 7:10 AM, Frodo Jedi wrote:
> Dear all,
> how can I perform a post hoc analysis for ANOVA with repeated measures (in
> presence of a balanced design
My suggestion is that you take the weekend lull in readership to now
read the Posting Guide which it appears you nave not yet done. Had you
done so you should have encountered the advice about how to
successfully attach data files. (None came through.) You would also
have read the request t
Dear all,
how can I perform a post hoc analysis for ANOVA with repeated measures (in
presence of a balanced design)?
I am not able to find a good example over internet in R...is there among you
someone so kind to give
me an hint with a R example please?
For example, the aov result of my analysis
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Dear [R] Users,
I have implemented a linear model with this syntax:
model<- lm (var_dependent ~ var_indipendent + factor + var_indipendent :
factor, dataframe)
anova (model)
Response: var_dependent
Df Sum Sq Mean Sq F value
Pr(>F)
Hi all,
Issue: I merged two zoo objects (a regular and an irregular). After the
merge I used the function 'na.approx' to have also values in the resolution
of the regular time series.
Problem: After approximation some rows at the beginning or at the end of the
zoo objects disappear due to t
On Mon, Nov 1, 2010 at 11:14 AM, Salim Alexander (salimale)
wrote:
> Hi all,
>
> Issue: I merged two zoo objects (a regular and an irregular). After the merge
> I used the function 'na.approx' to have also values in the resolution of the
> regular time series.
>
> Problem: After approximation so
Hi all,
Issue: I merged two zoo objects (a regular and an irregular). After the merge I
used the function 'na.approx' to have also values in the resolution of the
regular time series.
Problem: After approximation some rows at the beginning or at the end of the
zoo objects disappear due to the
See if rowttests is any faster.
library(genefilter)
?rowttests
You have to install Bioconductor. I've used this on large datasets,
but I haven't compared
timings.
On Mon, Sep 13, 2010 at 4:26 PM, Alexey Ush wrote:
> Hello,
>
> I have a question regarding how to speed up the t.test on large dat
Have a look at:
"Computing Thousands of Test Statistics Simultaneously in R" by Holger
Schwender and Tina Müller, in
http://stat-computing.org/newsletter/issues/scgn-18-1.pdf
Hadley
On Mon, Sep 13, 2010 at 4:26 PM, Alexey Ush wrote:
> Hello,
>
> I have a question regarding how to speed up the t
Hello,
I have a question regarding how to speed up the t.test on large dataset. For
example, I have a table "tab" which looks like:
a b c d e f g h
1
2
3
4
5
...
10
dim(tab) is 10 x 100
I need to do the t.test for each ro
Thanks, that seems to have cleared it up.
(I did cut and paste from the console - I didn't think most of what I tried
was very going to be very helpful and didn't want to drown people in
spurious info. Sorry for the mistakes)
--
View this message in context:
http://r.789695.n4.nabble.com/post
On Jul 21, 2010, at 6:36 PM, SNAFU1 wrote:
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 a
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
Dear Dennis,
thank you for your fast response. Perhaps I should have described the
experimental situation in more detail.
> This tells you that Subject is being treated as a random block
> factor, and that
> Conditions 1 and 2 are combinations of treatments applied to each
> subject. In
> o
Hi,
I am performing experiments in the field of visual perception where
we often apply balanced designs. Within a group of normal subjects,
we vary different stimulus conditions (like contrast, luminance,
temporal frequency of stimulation) and derive some psychophysical or
electrophysiolog
no one?
any pointers would really be greatly appreciated!
thanks,
kay
-
Kay Cichini
Postgraduate student
Institute of Botany
Univ. of Innsbruck
--
View this message in context:
http://r.789695.n4.nabble.com/post-hoc-t-tests-for-lme-lmer-m
hello,
i searched archives for post-hocs on mixed models and wondered why the
method which intuitively came up to me as first, namely reordering the
levels of the fixed factors and to examine the t-statistics (my model
contains only categorical factors, one with 2 and one with 4 levels), does
n
Hello David,
I wanted to thank you for pointing to this code for performing posthoc
friedman test. I just used this example to create a function to perform this
test (and also added some illustrative flexible plots to the mix), here:
http://www.r-statistics.com/2010/02/post-hoc-analysis-for-friedma
I have done ancova with categorical and continuous predictor variables.
The categorical predictor variable shows significant effect on the dependent
variable.
I would like to do a post-hoc test to see which groups in the categorical
variable differ.
I have explored Tukey test in multcomp package.
Anastasia wrote:
> Dear all,
>
> I have the following problem which I cannot solve:
>
> data <- numeric (100)
> for (i in 1:100){
> p <- runif(1,min=0,max=1)
> data[i] <- rnorm(1,mean=2,sd=1)
> }
Er what is "p" doing in there. As far as I can see, you might as well do
data <- rnorm(200, 2,
Dear all,
I have the following problem which I cannot solve:
data <- numeric (100)
for (i in 1:100){
p <- runif(1,min=0,max=1)
data[i] <- rnorm(1,mean=2,sd=1)
}
ke <- density(data,bw="sj",n=61)
How can I now find the value of this density function for example ke(0),
ke(2) etc.
Maybe this is
ettmansperger in ANZ J Stat a few years ago where they look at the decomposition of the
KW test into paired tests and 'non-transitivity' components.
-thomas
Michael
-Original Message-
From: Robert Kalicki
Sent: Mittwoch, 14. Oktober 2009 14:11
To: Meyners,Michael,
ael
> -Original Message-
> From: Robert Kalicki
> Sent: Mittwoch, 14. Oktober 2009 14:11
> To: Meyners,Michael,LAUSANNE,AppliedMathematics
> Subject: RE: [R] post-hoc test with kruskal.test()
>
> Hi Michael,
> Thank you very much for your clear and prompt answ
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