similar to: How to test the difference between paired correlations?

Thank you, but this now sounds more difficult: what would be the point in having these ready-made functions if I have to do it manually? Anyway, How would I implement the last part? On Thu, Mar 23, 2023 at 1:23?AM Ebert,Timothy Aaron <tebert at ufl.edu> wrote: > > If you are open to other options: > The null hypothesis is that there is no difference. > If I have two equations

My guess: It I clear from the link that they can use the R logo for commercial purposes. The issue is what to do about the "appropriate credit" and "link to the license." How would I do that on a hoodie? Would they need a web address or something? -----Original Message----- From: R-help <r-help-bounces at r-project.org> On Behalf Of John Fox Sent: Tuesday, March 21, 2023

I may be missing something but using the plain old c() combine function seems to work fine: df <- data.frame(left = 1:5, right = 6:10) df.combined <- data.frame(comb = c(df$left, df$right)) df left right 1 1 6 2 2 7 3 3 8 4 4 9 5 5 10 df.combined comb 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 -----Original

Sorry about that, let me check the correct version for the intrin0.h include guard. //Marcus ________________________________ From: Ralph Giles <giles at thaumas.net> Sent: Thursday, June 11, 2020 19:31 To: Marcus Asteborg <xnorpx at outlook.com>; opus at xiph.org <opus at xiph.org> Subject: Re: [opus] Misc patches Speaking of needing more complete ci feedback, the intrin0.h

Hi, You were on the right track using stack(), but you just pass the entire data frame as a single object, not the separate columns: > stack(NamesWide) ? values ? ind 1 ? ?Tom Name1 2 ? Dick Name1 3 ?Larry Name2 4 ?Curly Name2 Note that stack also returns the index (second column of 'ind' values), which tells you which column in the source data frame the stacked values originated

Hello everbody, I want to generate different subsets of my data-set and safe this subsets with names listet in a vector. Because in reality I have got about 70 subsets I want to realize this in a loop Somehow like this: names=c("nam1",

Just to repeat: you have NamesWide<-data.frame(Name1=c("Tom","Dick"),Name2=c("Larry","Curly")) and you want NamesLong<-data.frame(Names=c("Tom","Dick","Larry","Curly")) There must be something I am missing, because NamesLong <- data.frame(Names = c(NamesWide$Name1, NamesWide$Name2)) appears to

Hi guys, I am using the cor() function to see if there are correlations between March cortisol levels and December cortisol levels and I'm trying to figure out if the function is doing what I want it to do. Each sample has it's own separate row in the CSV file that I'm working out of. March Cort and December Cort are different columns and they come from separate samples, therefore

We are currently analyzing data on children clustered in day care-centers (DCC). We have tried to use geepack and gee libraries to estimate an overall incidence rate for absences (=number of absences/risk time) by specifying geese(number.absences ~ offset(log(risktime)), id=day.care.id, family=poisson("log"), data=dcc, corstr="exch",

Hi, Here are 3 suggested patches. 1. Build test for cmake and run the test in gitlab-ci. 2. Disable the message box on Windows on abort that cause test hangs in CI. 3. Build time improvement by removing unnecessary includes of stdio.h in production code and change to a lighter header intrin.h -> intrin0.h (windows only). Attached screenshot of measurement but it resulted in 14%

I suggest to add a new function to create a vector of n ``contiguous'' colors with tails in two colors. This function is similar to `cm.colors' but the colors can be choosen by hsv values. This function could be used e.g. as alternative to the default ``col.regions'' in `levelplot'. Perhaps the arguments in the following code could be simplified. Wolfram Fischer #---

While using the Hodges Lehmann Mean in DescTools (DescTools::HodgesLehmann), I found that it generated incorrect answers (see <https://github.com/AndriSignorell/DescTools/issues/97> https://github.com/AndriSignorell/DescTools/issues/97). The error is driven by the existence of tied values forcing wilcox.test in Base R to switch to an approximate algorithm that returns incorrect results - see

Greetings, I am having a problem with DescTools::Quantile (a function computing quantiles from weighted samples): # these sum to one probWeights = c( 0.0043, 0.0062, 0.0087, 0.0119, 0.0157, 0.0204, 0.0257, 0.0315, 0.0378, 0.0441, 0.0501, 0.0556, 0.06, 0.0632, 0.0648, 0.0648, 0.0632, 0.06, 0.0556, 0.0501, 0.0441, 0.0378, 0.0315, 0.0257, 0.0204, 0.0157, 0.0119, 0.0087,

It looks like a homework assignment. It also looks like you didn't read the documentation carefully enough. The 'len.out' argument in seq is solely for specifying the length of a sequence. The 'quantile' function omputes the empirical quantile of raw data in the vector 'x' at cumulative probabilit(y)(ies) given in the weights' argument, with interpolation I'm

Hi Everyone, Following the previous discussion on optimizing *wilcox functions, Andreas Loeffler brought to my attention a few other bugs in `wilcox` family functions. It seems like these issues have been discussed online in the past few months, but I haven?t seen discussion on R-devel...unless I missed an email, it seems like discussion never made it to the mailing list. I haven?t seen any bug

¿Alguien sabe si el test de reacciones extremas de Moses está escrito en algún paquete de R? Gracias de antemano.

Hello! I want to calculate simultaneous confidence intervals for a nominal variable with three categories: "yes", "no", "partially" and I expect that far more than 5 samples fall into each category. I have read that Glaz & Sison's method is only appropriate for variables with 7 or more categories. Therefore, the Goodman method seems like a good idea. I have

Verified that intrin0.h was available in 1910, by building it locally on VS2017 version 15.0 MSVC++ 14.1 _MSC_VER == 1910 (Visual Studio 2017 version 15.0) https://en.wikipedia.org/wiki/Microsoft_Visual_C%2B%2B //Marcus ________________________________ From: Marcus Asteborg <xnorpx at outlook.com> Sent: Thursday, June 11, 2020 20:15 To: Ralph Giles <giles at thaumas.net>; opus at

Dear Rusers, I tried to implement a function comparing mean scores between one subject (the patient) and a group a control subjects. The function returns attended results, but I also obtained the following warning : Warning message: the condition has length > 1 and only the first element will be used in: if (substr(fp, 1, 1) == "<") fp else paste("=", fp) Maybe

I am doing a cluster analysis with hclust. I want to get hclust to output the Hotelling's T squared statistic for each cluster so I can evaluate is data points should be in a cluster or not. My research to answer this question has been unsuccessful. Does anyone know how to get hclust to output the Hotelling's T squared statistic for each cluster? Mike [[alternative HTML version