search for: qtukey

Dear all, I'm using R to perform multiple comparison testing on agriculture genotype trials. To perform the Duncan's MRT, I use the qtukey() function with the following syntax: qtukey(p = ((1 - 0.05) ^ (pos - 1)), nmeans = pos, df = ni) I experience a strange behaviour when the number of means in the trial and the number of residual degrees of freedom (ni) becomes high (orientatively pos > 30 and ni > 60), i.e. the function...

...ooled?within?samplevariance is used throughout." So the connection is nranges == r, and nmeans == c. (n never actually factors in because sqrt(n) is part of the standardization) For the typical application, r is 1 for the usual studentized range distribution. E.g. for two large groups: > qtukey(.95,2,df=Inf) [1] 2.771808 As there is only one difference to consider, this should be distributed like the absolute value of the difference between two standard normals, and yes: We get our old friend 1.96 from > qtukey(.95,2,df=Inf)/sqrt(2) [1] 1.959964 It is less than fortunate that the he...

Dear all, I wanted to compare Bonferroni vs TukeyHSD correction over a range of groups and group sizes, and wanted to use the function qtukey. In the help documentation it says qtukey(p, nmeans, df, nranges = 1, lower.tail = TRUE, log.p = FALSE) Arguments q vector of quantiles. p vector of probabilities. nmeans sample size for range (same for each group). df degrees of freedom for s (see below). nranges number of groups whose...

Hi, I'm building Tukey's table using qtukey function. It happens that I can't get the values of Tukey's one degree of freedom and also wanted to eliminate the first column. The program is: Trat <- c(1:30) # number of treatments gl <- c(1:30, 40, 60, 120) # degree freedom tukval <- matrix(0, nr=le...

...x.html -- Sent from my phone. Please excuse my brevity. On July 6, 2017 11:36:47 AM PDT, Ursula Garczarek <Ursula.Garczarek at cytel.com> wrote: >Dear all, >I wanted to compare Bonferroni vs TukeyHSD correction over a range of >groups and group sizes, and wanted to use the function qtukey. > >In the help documentation it says > >qtukey(p, nmeans, df, nranges = 1, lower.tail = TRUE, log.p = FALSE) >Arguments >q > >vector of quantiles. > >p > >vector of probabilities. > >nmeans > >sample size for range (same for each group). > >df...

I am embarrassed to have to ask this but can anyone tell me of a Tukey multiple comparisons procedure available for R? I have looked through the search page, through the FAQ, and in the index of V&R (1999), and I still can't find such a thing. I see there is a ptukey function and a qtukey function but that is as far as I got. Do I need to roll my own? -- Douglas Bates bates at stat.wisc.edu Statistics Department 608/262-2598 University of Wisconsin - Madison http://www.stat.wisc.edu/~bates/ -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-....

...phyper.o plnorm.o plogis.o pnbeta.o pnbinom.o pnchisq.o pnf.o pnmath.o pnorm.o pnt.o polygamma.o ppois.o pt.o ptukey.o punif.o pweibull.o qbeta.o qbinom.o qcauchy.o qchisq.o qexp.o qf.o qgamma.o qgeom.o qhyper.o qlnorm.o qlogis.o qnbeta.o qnbinom.o qnchisq.o qnf.o qnorm.o qnt.o qpois.o qt.o qtukey.o qunif.o qweibull.o sign.o stirlerr.o toms708.o -lgomp -F/Library/Frameworks/R.framework/.. - framework R -Wl,-framework -Wl,CoreFoundation ld: warning, duplicate dylib /Developer/SDKs/MacOSX10.4u.sdk/usr/local/ lib/libgcc_s.1.dylib ** arch - ppc ... gcc -arch ppc -isysroot /Developer/SDKs/Ma...

...y/stats/R/TukeyHSD.R r-local/R/src/library/stats/R/TukeyHSD.R --- r-devel/R/src/library/stats/R/TukeyHSD.R 2005-07-14 23:13:49.000000000 -0300 +++ r-local/R/src/library/stats/R/TukeyHSD.R 2005-07-15 02:43:25.055207448 -0300 @@ -66,10 +66,12 @@ center <- center[keep] width <- qtukey(conf.level, length(means), x$df.residual) * sqrt((MSE/2) * outer(1/n, 1/n, "+"))[keep] - dnames <- list(NULL, c("diff", "lwr", "upr")) + est <- center/(sqrt((MSE/2) * outer(1/n, 1/n, "+"))[keep]) + pvals <-...

...;= Tstudent$conf.int[1:2][2]) { lst1[[1]] <- x lst <- c(lst,lst1) } else { lst1[[1]] <- x[1] lst2[[1]] <- x[2] lst <- c(lst,lst1) lst <- c(lst,lst2) } } else { test <- x[c(1,length(x))] Q <- (as.numeric(test[2]) - as.numeric(test[1]))/E qtt <- qtukey(0.95,length(x),df=41) if (Q < qtt) { lst1[[1]] <- range(x) lst <- c(lst,lst1) } else { x1 <- x[-length(x)] x2 <- x[-1] NK(x1) NK(x2) } } return(lst) } with > fm1 Call: aov(formula = vd ~ groupe, data = exple) Terms: groupe Residua...

...NULL resid(res2) doesn't work and reports NULL res2$df.residual doesn't work and reports NULL Is this an undocumented feature or an error? It sure plays havoc with Dr. Bates' contribution of Tukey.aov which works with res0 and res1 but doesn't work with res2 and reports Error in qtukey(p, nranges, nmeans, df, lower.tail, log.p) : Non-numeric argument to mathematical function A simple but inelegant workaround is to input mse and df.residual as function arguments in addition to the aov object. Does anyone have a better solution? Thank you, Peter B. -- Peter B. Mandevill...

....o qgeom.o rgeom.o dhyper.o phyper.o qhyper.o rhyper.o dnbinom.o pnbinom.o qnbinom.o rnbinom.o dpois.o ppois.o qpois.o rpois.o dweibull.o pweibull.o qweibull.o rweibull.o dlogis.o plogis.o qlogis.o rlogis.o dnchisq.o pnchisq.o qnchisq.o dnbeta.o pnbeta.o qnbeta.o pnf.o pnt.o qnf.o qnt.o ptukey.o qtukey.o toms708.o wilcox.o signrank.o ranlib libnmath.a config.status: creating src/unix/Makefile make: /usr/local/R-devel/srcunix: No such file or directory *** Error code 2 Stop in /usr/local/R-devel/src/unix. *** Error code 1 Stop in /usr/local/R-devel/src. *** Error code 1 Stop in /usr/local/R-dev...

...[-length(x)] a <- rep(y, times = y-1) mb <- matrix(1, length(x)-1, length(x)-1) rb <- row(mb) b <- rb[rb + col(mb) <= length(x)] rm(y, mb, rb) # # Compare diffs bt means with value from # tables; alpha=0.05 # q <- (x[a] - x[b]) / se qt <- qtukey(0.95, length(x), df) results <- ifelse(q >= qt, "diff *", "same") # # Generate output # tab <- cbind(round(q, digits=4), results) rownames(tab) <- paste("mean", a, "vs", "mean", b) rm(a, b) colnam...

...on. For while, it is running nice (Tukey and SNK), for simple design (completely randomized, randomized block and Latin squares) and simple experimental schemes (one factor). I'm needing only two informations: 'qduncan' and 'pduncan', similar to already available in R 'qtukey' and 'ptukey'. The basic algorithm implemented with SNK test will be used for Duncan test. Below a sample: a) Generating data and calling the function: tra = gl(4, 5, label = c('A', 'B', 'C', 'D')) blo = rep(1:5, 4) pro = c(NA, 26, 20, 23, 21, 31, 25...

hello, I need to groupe some means and I wonder how to do to get critical range table for tukey or for Neuman-Keuls I think it's possible to do that with the qtukey() function? thanks. _____________________________________________________________________________ [[alternative HTML version deleted]]

Hi, What is expression IC on TukeyHSD? contrast +/- qtukey(.95, nmeans, df) * sqrt(MSe/n) ? Thanks, Bruno [[alternative HTML version deleted]]

Hi, All: ** My previous email on this subject seemed to contain an error; check the correction: Is there a function in R to compute the expected range of a sample of size n from some distribution? I ask, because I was recently asked about the control chart constant 'd2', which is the expected range for a sample of size n from a standard normal. There is a fairly simple

Hi, the function TukeyHSD gives incorrect results for balanced incomplete block designs, as the example below shows, but I can only half fix it. There are two problems, 1. It uses model.tables to estimate treatment means, 2. It uses the wrong standard error The first problem can be fixed using dummy.coef, if the lines > TukeyHSD.aov function (x, which = seq(along = tabs), ordered = FALSE,

Hi, I have a simple dataset with repeated measures. one factor is treatment with 3 levels (treatment1, treatment2 and control), the other factor is time (15 time points). Each treatment group has 10 subjects with each followed up at each time points, the response variable is numeric, serum protein amount. So the between subject factor is treatment, and the within subject factor is time. I ran a

...-ieee_with_inexact -g -I../include -I../../src/include -c pnf.c -o pnf.o gcc -ieee_with_inexact -g -I../include -I../../src/include -c pnt.c -o pnt.o gcc -ieee_with_inexact -g -I../include -I../../src/include -c ptukey.c -o ptukey.o gcc -ieee_with_inexact -g -I../include -I../../src/include -c qtukey.c -o qtukey.o gcc -ieee_with_inexact -g -I../include -I../../src/include -c dwilcox.c -o dwilcox.o gcc -ieee_with_inexact -g -I../include -I../../src/include -c pwilcox.c -o pwilcox.o gcc -ieee_with_inexact -g -I../include -I../../src/include -c qwilcox.c -o qwilcox.o gcc -ieee_with_inexact...

...src/include -c dnbeta.c cc -ieee_with_inexact -g -I../../src/include -c pnbeta.c cc -ieee_with_inexact -g -I../../src/include -c pnf.c cc -ieee_with_inexact -g -I../../src/include -c pnt.c cc -ieee_with_inexact -g -I../../src/include -c ptukey.c cc -ieee_with_inexact -g -I../../src/include -c qtukey.c cc -ieee_with_inexact -g -I../../src/include -c dwilcox.c cc -ieee_with_inexact -g -I../../src/include -c pwilcox.c cc -ieee_with_inexact -g -I../../src/include -c qwilcox.c cc -ieee_with_inexact -g -I../../src/include -c rwilcox.c ar cr ../lib/libmath.a mlutils.o d1mach.o i1mach.o fmax2.o...