similar to: inheritance problem in multcomp package (PR#6978)

I have the following code: ``` rm(list=ls()) N = 30000 xvar <- runif(N, -10, 10) e <- rnorm(N, mean=0, sd=1) yvar <- 1 + 2*xvar + e plot(xvar,yvar) lmMod <- lm(yvar~xvar) print(summary(lmMod)) domain <- seq(min(xvar), max(xvar))??? # define a vector of x values to feed into model lines(domain, predict(lmMod, newdata = data.frame(xvar=domain)))??? # add regression line, using

Dear R-devel list members, I'd like to suggest a more flexible procedure for generating contrast names. I apologise for a relatively long message -- I want my proposal to be clear. I've never liked the current approach. For example, the names generated by contr.treatment paste factor to level names with no separation between the two; contr.sum simply numbers contrasts (I recall an

Hi list, I was searching how to properly write a command line for a mixed ANOVA. Well honestly, there are so many material on the older post of the list that just confused me. I have five factors. Season (fixed) Beach (fixed) Line (fixed) Block (random) Strata (random) nested in Block And for each of the tree strata per block I got 3 replicates. I saw lots of things about

Using a "by() statement, I am preparing ANOVA's for multiple experiments, and using simint() to generate confidence intervals. This works fine. simint.by.fit <- by(analytes.dfr, list(Assay = analytes.dfr$analyte ), function(data) (simint(value ~ tx, data = data,type='Tukey' ) ) ) I can separately prepare plots of the confidence intervals, and I can prepare separate plots

Dear R-developeRs, Attached follows a patch against svn 34959 that adds the printing of p-values to the TukeyHSD.aov function in stats package. I also updated the corresponding documentation file and added a 'see also' reference to the simint function of the multcomp package. As it was already brought up in a previous thread [1] in R-help, one can obtain the adjusted

Dear R-listers, I am trying to compute simultaneous confidence intervals with simint from the package multcomp. 230 measures (abundance) have been taken in 23 sites (factor) of a data.frame (donnees: a file can be sent on request, saved with save(donnees,file="donnees")). I would like to get all pairwise comparisons with : mc<- simint(ren~ID,type="Tukey",data=donnees) I

Hi all, I've done some anovas, found some significance and proceeded to do the post hoc tests to determine the source of the significance. I used the multcmp package as suggested by Andy Liaw (thank you). I am, however, unsure how to interpret the results of the call to simint. Could someone help me with this? I've attached the code and the results it produced. There are 3 groups

# R for Windows will not send your bug report automatically. # Please copy the bug report (after finishing it) to # your favorite email program and send it to # # r-bugs at r-project.org # ###################################################### This report is joint from Richard Heiberger <rmh at temple.edu> and Burt Holland <bholland at temple.edu>. Burt Holland is the coauthor

I am analyzing data from an experiment with two factors: Carbon (+/-) and O3 (+/-), with 4 replicates of each treatment, and 4 harvests over a year. The treatments are assigned in a block design to individual Rings. I have approaches this as a repeated measures design. Fixed factors are Carbon, O3 and Harvest, with Ring assigned as a random variable. I have performed repeated measures analysis

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]]

simint and TukeyHSD work for aov objects. Can someone point me to similar functions for lme objects? Dieter Menne

I am trying to find the best way to save the follwoing object I am creating library(multcomp) data(recovery) Dcirec<-simint(minutes~blanket, data=recovery, conf.level=0.9, alternative="less") I am probably not doing it the most efficient way I think. Here is what I am doing a<-print(Dcirec) write(a,file="mult_test.dat", append=T) or save(Dcirec,

Dear useRs, `multcomp' version 0.991-1 will be shortly available from CRAN near you. Nearly all functionality contained in the package has been re-implemented from scratch. The focus of the package has been extended to general linear hypotheses in arbitrary parametric models and the most important function to check out is `glht()'. Multiple comparison of means procedures (for example

Dear useRs, `multcomp' version 0.991-1 will be shortly available from CRAN near you. Nearly all functionality contained in the package has been re-implemented from scratch. The focus of the package has been extended to general linear hypotheses in arbitrary parametric models and the most important function to check out is `glht()'. Multiple comparison of means procedures (for example

New package `multcomp' for general multiple comparisons written by Frank Bretz, Torsten Hothorn and Peter Westfall We've uploaded the package `multcomp' to CRAN. The R package allows for multiple comparisons of k groups in general linear models. We use the unifying representations of multiple contrast tests, which include all common multiple comparison procedures, such as the

New package `multcomp' for general multiple comparisons written by Frank Bretz, Torsten Hothorn and Peter Westfall We've uploaded the package `multcomp' to CRAN. The R package allows for multiple comparisons of k groups in general linear models. We use the unifying representations of multiple contrast tests, which include all common multiple comparison procedures, such as the

Dear list, As a reply to my recent mail: > simint and TukeyHSD work for aov objects. > Can someone point me to similar functions for lme objects? Douglas Bates wrote There aren't multiple comparison methods for lme objects because it is not clear how to do multiple comparisons for these. I don't think the theory of multiple comparisons extends easily to lme models. One could

Here it is again, hope this is more clear I am using the following data (only a small subset is given): Habitat Fungus.yield Birch 20.83829053 Birch 22.9718181 Birch 22.28216829 Birch 24.23136797 Birch 22.32147961 Birch 20.30783598 Oak 27.24047258 Oak 29.7730014 Oak 30.12608508 Oak 25.76088669 Oak 30.14750974 Hornbeam 17.05307949 Hornbeam 15.32805111 Hornbeam 18.26920177 Hornbeam 21.30987049

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

Hi, I'm unable to get past the subject error trying to setup dovecot 2.1.10 on FreeBSD 6.4: right after login the server closes the connection (testing with telnet) I've tried manualy chown()ing auth-master to 666, so permission issues should be ruled out. I'm attaching logs, config and excerpt of ktrace -id. I've built a version with debug symbols, but I don't seem to hit a