similar to: Duncan's MRT: limitations to qtukey() function?

Well, it is clear enough that the problem is in interpreting the documentation. However, when you claim you tested something, and found it inconsistent with tables, it would be advisable to back it up with examples! The description in the help files and in the sources is admittedly confusing. The original paper has this, rather more clear, description in the abstract: "We consider the

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

We cannot help you understand what you are doing if you do not show us what you are doing. Here are some discussions about how to communicate questions about R [1][2][3]. [1] http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example [2] http://adv-r.had.co.nz/Reproducibility.html [3] https://cran.r-project.org/web/packages/reprex/index.html -- Sent from my phone.

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

I am using R 1.1 with Redhat 6.2 and RW 1.001 with Win98 (the upkey doesn't work on my IBM either as has been previously reported by others). The function aov doesn't return either the residuals or the residual degrees of freedom for split-plot designs. If you use the following code from Baron and Li's "Notes on the use of R for psycology experiments and questionnaires"

(1) ...need to speed up a monte-carlo sampling...any suggestions about how I can get R to use all 8 cores of a mac pro would be most useful and very appreciated... (2) spent the last few hours trying to get pnmath to compile under os- x 10.5.4... using gcc version 4.2.1 (Apple Inc. build 5553) as downloaded from CRAN, xcode 3.0... ...xcode 3.1 installed over top of above after

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=length(gl), nc=length(Trat)) for(i in

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

On a recent FreeBSD 8.0-CURRENT (i386) building R (any version) breaks with the following messages: ---------------------------------------------------------------------- [...snip...] gcc -std=gnu99 -I. -I../../src/include -I../../src/include -I/usr/local/include -DHAVE_CONFIG_H -g -O2 -c wilcox.c -o wilcox.o gcc -std=gnu99 -I. -I../../src/include -I../../src/include -I/usr/local/include

Dears members of R list, I would like that a more experienced R user help me to complete this analysis: r = gl(3, 8, label = c('r1', 'r2', 'r3')) e = rep(gl(2, 4, label = c('e1', 'e2')), 3) y = c(26.2, 26.0, 25.0, 25.4, 24.8, 24.6, 26.7, 25.2, 25.7, 26.3, 25.1, 26.4, 19.6, 21.1, 19.0, 18.6, 22.8, 19.4, 18.8, 19.2, 19.8, 21.4, 22.8, 21.3) df =

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

hello, I have programmed this function to calculate the Neuman-Keuls test but I have a problem the function return an empty list and I don't know why. summary(fm1) E <- sqrt((summary(fm1)[[1]]["Residuals","Mean Sq"])/length(LR)) lst <- list() lst1 <- list() lst2 <- list() NK <- function (x) { if (length(x) == 2) { Tstudent <- t.test(subset(exple,

That makes sense to me. The field needs to be split into bytes. The low byte is the integer part of voltags, and the high part is units of 10 mV. And this is per cell. Probably the unit is measuring the total and then dividing by 36. But volts per cell will have the same interpretation for varying cell counts, so it's a nice representation.

I suppose, this approach may be apply to some other data from that UPS. I could check another values and ask powercom support for other data items to explain interpretation, if it will help. On 13.01.23 14:22, Greg Troxel wrote: > That makes sense to me. The field needs to be split into bytes. The > low byte is the integer part of voltags, and the high part is units of > 10 mV. And

Hello! I left this line uncommented in powercom-hid.c for battery voltage: { "battery.voltage", 0, 0, "UPS.Battery.Voltage", NULL, "%.2f", 0, NULL }, and got some data different from the input voltage values The Powercom support staff gave the following response to my question: Dear Alex, First of all , thank you for purchasing PCM MRT-3000 ups. Regarding of your

Hi, In this newsletter (Vol 7, 1),the article on AMMI by Onofri and Ciriofolo presented a AMMI function. One of arguments for this function AMMI (Page 17) is biplot. There is a biplot fucntion from {stats} package. I guess they are not the same. Could the authors clarify that? Thanks, Yuandan [[alternative HTML version deleted]]

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

Hei, i am trying to plot the means of two variables (d13C and d15N), by 2 grouping factors (Species and Year) that i obtained by the function tapply. I would like to plot with different colours according to the Year and show the "Species" as data labels. My data looks like this: Species d13C d13N Year "Species1" 14,4 11.5 2009 "Species2"

Hi to all, I''m using an Effect.Appear on a div that have a PNG 24 (with alpha transparency). Works prefectly on all excecpt... IE6 that do not render alpha channel on PNGs. So I wrote a conditional comment to apply the propietary IE filter to load alpha adding filter: in a style tag. Well, during Effect.Appear, appear a black png background on the alpha. Have workarounds or tips to fix

Dears members of R list, It would like that a more experienced statician in R helped me to complete the analysis to follow: r = gl(3, 8, label = c('r1', 'r2', 'r3')) e = rep(gl(2, 4, label = c('e1', 'e2')), 3) y = c(26.2, 26.0, 25.0, 25.4, 24.8, 24.6, 26.7, 25.2, 25.7, 26.3, 25.1, 26.4, 19.6, 21.1, 19.0, 18.6, 22.8, 19.4, 18.8, 19.2, 19.8, 21.4,