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Dear all, I'm writing my manuscript to publish after analysis my final data with ANOVA, ANCOVA, MANCOVA. In a section of my result, I did correlation of my data (2 categirical factors with 2 levels: Quantity & Quality; 2 dependent var: Irid.area & Casa.PC1, and 1 co-var: SL). But as some traits (here Irid.area) are significantly influenced by the covariate (standard length, SL), I

In using cor(data.frame), it is annoying that you have to explicitly filter out non-numeric columns, and when you don't, the error message is misleading: > cor(iris) Error in cor(iris) : missing observations in cov/cor In addition: Warning message: In cor(iris) : NAs introduced by coercion It would be nicer if stats:::cor() did the equivalent *itself* of the following for a data.frame:

?s 17:39 de 25/07/2024, Yuan Chun Ding via R-help escreveu: > Hi R users, > > I generated a square correlation matrix for the dat dataframe below; > dat<-data.frame(g1=c(1,0,0,1,1,1,0,0,0), > g2=c(0,1,0,1,0,1,1,0,0), > g3=c(1,1,0,0,0,1,0,0,0), > g4=c(0,1,0,1,1,1,1,1,0)) > library("Hmisc") > dat.rcorr =

Hi UseRs, I don't want to die beeing idiot... I dont understand the different results between: cor() and cov2cov(cov()). See this little example: > x=matrix(c(0.5,0.2,0.3,0.1,0.4,NA,0.7,0.2,0.6,0.1,0.4,0.9),ncol=3) > cov2cor(cov(x,use="pairwise.complete.obs")) [,1] [,2] [,3] [1,] 1.0000000 0.4653400 -0.1159542 [2,] 0.4653400 1.0000000

HI Rui, Thank you for the help! You did not remove a row if zero values exist in both column pair, right? Ding From: Rui Barradas <ruipbarradas at sapo.pt> Sent: Thursday, July 25, 2024 11:15 AM To: Yuan Chun Ding <ycding at coh.org>; r-help at r-project.org Subject: Re: [R] please help generate a square correlation matrix ?s 17:?39 de 25/07/2024, Yuan Chun Ding via R-help

?Hola, A mí me funciona la importación directa. Previamente he guardado la hoja de Excel en .csv (separado por ";"). Y hago sin problemas la correlación entre dos variables (las dos primeras). > datIn <- read.csv("Variables.csv", header=T, as.is=T, sep=";", dec=",") > head(datIn) EMPRESAS AA AB AC AD AE AF AG AH AI

Dear R What does NaN mean? I recently did a correlation on a batch of data for some reason it didn't like one column cor(sleep,use="complete.obs") BodyWt BrainWt SlowSleep ParaSleep TotalSleep BodyWt 1.00000000 0.95584875 -0.3936373 -0.07488845 -0.3428373 BrainWt 0.95584875 1.00000000 -0.3867947 -0.07427740 -0.3370815 SlowSleep -0.39363729

Has probado con cor(datos,use="pairwise.complete.obs") ??? > From: valeagui en outlook.es > To: cof en qualityexcellence.es; r-help-es en r-project.org > Date: Wed, 11 Nov 2015 15:13:55 +0000 > Subject: Re: [R-es] Problema con la lectura de datos > > Hola Carlos, muchas gracias....pero hago exactamente lo mismo que tu..y al intentar de hacer la matriz de

Hola. He estado viendo los datos que adjuntas en el correo. Al ser un fichero Excel xlsx ¿por qué no lo abres directamente? Te aconsejaría la librería openxlsx (si no la has usado nunca , instálala con install.packages(?openxlsx?)) Este es el código que he ejecutado y los resultados que obtengo: library(openxlsx) dat <- read.xlsx("Variables.xlsx") str(dat) Que produce:

Friends I am new to R (and statistics) so am struggling a bit. Briefly... I am interested in getting the P-Value from cor(X) where X is a matrix. I have found cor.test. Verbosely... I have 4 vectors and can generate the corellation matrix... > cor(cbind(X1, X2, X3, X4)) X1 X2 X3 X4 X1 1.00000000 -0.06190365 -0.156972795 0.182547517 X2

I tried 2 methods to estimate C.I. of correlation coefficient of variables x and y: > x <- c(44.4, 45.9, 41.9, 53.3, 44.7, 44.1, 50.7, 45.2, 60.1) > y <- c( 2.6, 3.1, 2.5, 5.0, 3.6, 4.0, 5.2, 2.8, 3.8) #METHOD 1: Pearson's ********************************************************** > cor.test(x, y, method = "pearson", conf.level = 0.95) Pearson's

Hi Rui, You are always very helpful!! Thank you, I just modified your R codes to remove a row with zero values in both column pair as below for my real data. Ding dat<-gene22mut.coded r <- P <- matrix(NA, nrow = 22L, ncol = 22L, dimnames = list(names(dat), names(dat))) for(i in 1:22) { #i=1 x <- dat[[i]] for(j in (1:22)) { #j=2 if(i == j) { #

Si lo has guardado como csv separado por comas: Abre con cualquier editor el fichero: mira separador de listas y separador de decimal, supongamos que sea "; " para las listas (esto depende de tu configuración regional) y "." para los decimales (es como lo tienes en tu fichero) entonces dat<-read.csv("Variables.csv", header=T, sep=";",

?s 20:47 de 25/07/2024, Yuan Chun Ding escreveu: > Hi Rui, > > You are always very helpful!! Thank you, > > I just modified your R codes to remove a row with zero values in both column pair as below for my real data. > > Ding > > dat<-gene22mut.coded > r <- P <- matrix(NA, nrow = 22L, ncol = 22L, > dimnames = list(names(dat),

Dear All, I faced the following problem. With the same data.frame the results are different under Linux and Windows. Could you help on this topic? Thanks in advance, Ildiko Linux: > d = read.csv("CRP.csv") > d$drugCode = as.numeric(d$drug) > cor(d, use="pairwise.complete.obs") PATIENT BL.CRP X24HR.CRP X48HR.CRP drug drugCode PATIENT NA

If I have understood the request, I'm not sure that omitting all 0 pairs for each pair of columns makes much sense, but be that as it may, here's another way to do it by using the 'FUN' argument of combn to encapsulate any calculations that you do. I just use cor() as the calculation -- you can use anything you like that takes two vectors of 0's and 1's and produces fixed

Hi all, I have a data set (df, n=10 for the sake of simplicity here) where I have two continuous variables (age and weight) and I also have a grouping variable (group, with two levels). I want to run correlations for each group separately (kind of similar to "split file" in SPSS). I've been experimenting with different functions, and I was able to do this correctly using ddply

Let's go back to the original posting. > > > >> in each column, less than 10% values are 1, most of them are 0; > > > > > > > >> so I want to remove a row with value of zero in both columns when calculate correlation between two columns. > > So we're talking about correlations between binary variables. Suppose we have two 0-1-valued

I am producing 2X2 correlation matrices by a class variable. I need to extract a vector of correlation coefficients only. I am doing that in a loop (see below) but I am sure there would be a simpler way. Please help! > by(d1[,c(2,3)],d1[,1],cor) d1[, 1]: 1 c e c 1.0000000 0.1972309 e 0.1972309 1.0000000

Greetings: It would seem to me that the three arguments "a", "c" and "p" ought to produce the same result with a data frame that doesn't have any missing data which is not the case. What am I doing wrong or what don't I understand? > tmp <- data.frame(vol,con,mot,esp,pri,sec) > tmp vol con mot esp pri sec 1 1.00 120 90 78 21 1 2 0.50