search for: dunnett

...es gcc, perl,bin, helpwrk and rw1040. I got rw1040 from BDR place, the rest were gotter from the internet in the last week of the year, i.e. they are the newest versions. I modified autoexec.bat to put gcc\bin, perl\bin, etc in the path. I put the BDR util.zip programs in bin. I created a directory Dunnett with subdirectories src, r, man in c:/r/rw1040/src/library. I opened the dos window cd to c:/r/rw1040/src/gnuwin32 and type make libR.a it works and created a libR.a of 1.1 Mb Then I typed: Rcmd INSTALL c:/r/rw1040/src/library/Dunnett and got : make: Entering directory '/cygdrive/c/r/rw1040/...

Hi, I've got a data set with a control group and a number of experimental groups, that have unequal sample sizes, and am measuring the number of people in each that respond yes or no. I'd like to use a dunnett test in R, where the syntax is supposed to be like: library(multcomp) test.dunnett=glht(anova_results,linfct=mcp(method="Dunnett")) confint(test.dunnett) plot(test.dunnett) but: 1) How do I run a dunnett test without doing the ANOVA (which wouldn't have its requirements satisfied,...

Hi! I use simtest fonction of multcomp package to compile a Dunnett's test. I have 10 treatments and one control group, so i create a matrix with: m<-matrix(0,10,11) m[1,1]<--1 m[1,2]<-1 m[2,1]<--1 m[2,3]<-1 m[3,1]<--1 m[3,4]<-1 m[4,1]<--1 m[4,5]<-1 m[5,1]<--1 m[5,6]<-1 m[6,1]<--1 m[6,7]<-1 m[7,1]<--1 m[7,8]<-1 m[8,...

Hi, all: Two examples are shown below. I want to use the multiple comparison of Dunnett. It succeeded in upper case "example 1". However, the lower case "example 2" went wrong. In "example 2", the function pmvt return NaN, so I cannot show this simtest result. Is there any solution? (I changed the variable "maxpts" to a large number in fron...

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...

...$hama,gad$dosegrp,summaryfn)   #### ANOVA ####   model1 <- aov(hama~dosegrp,data=gad) summary.aov(model1)   #### Multiple Comparisons ####   library(multcomp)   #### Pairwise T-Tests ####   cht <- glht(model1, linfct = mcp(dosegrp = "Tukey")) summary(cht, test = univariate())   #### Dunnett's Test ####   #Not sure how to set the reference group to placebo #cht <- glht(model1, linfct = mcp(dosegrp = "Dunnett")) #summary(cht, test = univariate())   model2 <- aov(hama ~ dosegrp - 1, data = gad) K <- rbind(c(1, 0, -1), c(0, 1, -1)) rownames(K) <- c("HI vs PL...

Hi, I want to retrieve a value in the Dunnett's tables. I know the comparisons type, the percent of level,the number of traitments and the degrees of freedom. Is there a function to retrieve this value with this? Laurent Houdusse Analyste Programmeur

...# 5 levels > d$time <- as.factor(d$time) # 2 levels > d$batch <- as.factor(d$batch) # 3 levels the data frame d contains 82 rows. There are 2 to 4 replicates of each dose within each time point and each batch. There's one dose completely missing from one batch. I then generate Dunnett contrasts using the multicomp library: > contrasts(d$dose) <- contr.Dunnett(levels(d$dose), 1) > contrasts(d$time) <- contr.Dunnett(levels(d$time), 1) > contrasts(d$batch) <- contr.Dunnett(levels(d$batch), 1) For the moment I'm just looking at the dose effects of the complet...

...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 'glht' for the above amod. I know that I cannot use simply glht(amod, linfct = mcp(f = "Dunnett")). Also, if I want to use Dunnett for comparing C vs (T1 and T2), how can I specify this in the glht function. Thanks in advance. Regards, Ezhil

...t;package:lattice" [9] "package:grid" "Autoloads" "package:base" > ## from R/rw1091alpha/library/multcomp/R-ex/simint.R > data(recovery) > lmmod <- lm(minutes ~ blanket, data=recovery, contrasts=list(blanket = + "contr.Dunnett")) > summary(simint(lmmod, psubset=2:4, conf.level=0.9, + alternative="less",eps=0.0001)) Simultaneous 90% confidence intervals: model contrasts model contrasts for factor Contrast matrix: [,1] [,2] [,3] [1,] 1 0 0 [2,] 0 1 0 [3,] 0...

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 "coef." Error in modelparm.default(model, ...) : no 'coef' method for 'model' found! Thanks! Regards, Anqi Qiu Assistant Professor Div...

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 "coef." Error in modelparm.default(model, ...) : no 'coef' method for 'model' found! Thanks! Regards, Anqi Qiu Anqi Qiu Center for Imaging...

Hola. Hay alguna función que haga un Friedman test (digamos 4 tratamientos o tiempos relacionados/dependientes) y que después haga una comparación de un tratamiento contra el resto, digamos el primero, como un contratase simple, o un Dunnett? o simplemente ¿como hago un Dunnett para unos tratamientos relacionados? -- Antonio M [[alternative HTML version deleted]]

...proof of concept, we plan to implement a test for a given experiment. Its design split data into 10 groups (including a control one) with 2 mesures for each (ref at t0 and response at t1). We aim to compare each group response with control response (group 1) using a multiple comparison procedure (Dunnett test). Before achieving this, we have to normalize our data : response values cannot be compared if base line isn't corrected. Covariance analysis seems to represent the best way to do this. But how to perform this by using R ? Actually, we have identify some R functions of interest regarding...

Hello ALL: I am looking for multiple comparison tests for ANOVA models. Does R have any of these? Fisher least significant difference test. Tukey henestly significant difference test. Newman - Keul test. Dunnett's test Scheffe test. Thank you, ANDREW -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body&quot...

...proof of concept, we plan to implement a test for a given experiment. Its design split data into 10 groups (including a control one) with 2 mesures for each (ref at t0 and response at t1). We aim to compare each group response with control response (group 1) using a multiple comparison procedure (Dunnett test). Before achieving this, we have to normalize our data : response values cannot be compared if base line isn't corrected. Covariance analysis seems to represent the best way to do this. But how to perform this by using R ? Actually, we have identify some R functions of interest regarding...

Hello, I am interested in parametric multi comparison tests such as Dunnett, Duncan, Tukey, Newman-Keuls, Bonferonni, Scheffe, and non-parametric tests such as Kruskal-Wallis, and Mann-Whitney U. Are there packages that include most of these tests in each category? Many packages exist for an individual test but their outputs vary in great detail (test statistics, p-values...

...send a copy to r-help I will not repeat it here. Suffice to say that adding data=data.frame(x,g,s) works well and no more problems. Thanks Thomas. Now here there is another problem with my program to compute multiple comparisons. From App.Stat I have a fortran program to compute the probability for Dunnett tests. I compiled it to a dll and it works well, no problems there. Now I need the inverse 'qdunnett' and I decided that an easy way |:-)) was to use nls to find the point. something similar to: > alpha<-0.05 > df<-10 > nls.control() $maxiter [1] 50 $tol [1] 1e-05 $minF...

Hello, R users, I have a dataset that looks like this: id var1 var2 1 1 3 2 3 1 3 2 1 4 1 2 5 2 3 I want to split one column to two columns with 1 = 1 and 1, 2 = 1 and 2, 3 = 2 and 2: id var1.1 var1.2 var2.1 var2.2 1 1 1 2 2 2 2 2 1 1 3 1 2

Greetings all, I've done some ANOVAs and have found significant effects across my groups, so now I have to do some post-hoc tests to ascertain which of the groups is driving the significant effect. Usually one would do something like a Newman-Keuls or Scheffe test to get at this but based on googling and browsing through the r-help archives R doesn't support these and they seem to be