similar to: How to test frequency independence (in a 2 by 2 table) with many missing values

Hello all, I wish to perform a mcnemar test for a 3 by 3 matrix. By running the slandered R command I am getting a result but I am not sure I am getting the correct one. Here is an example code: (tt <- as.table(t(matrix(c(1,4,1 , 0,5,5, 3,1,5), ncol = 3)))) mcnemar.test(tt, correct=T) #And I get: McNemar's Chi-squared

Hello all I wish to perform a mcnemar.test() for a 5X5 matrix. Wikipedia tells me (http://en.wikipedia.org/wiki/Cochran_test) I should turn to cochran.test. The only place I found it was in the "outliers" package, but the command cochran.test() acts differently then mcnemar.test() , and doesn't take a table as input. Any ideas on how to use it ? #Example code: aa =

Dear R-users, i try to generate missing values in a matrix X according to a given missingnes pattern R with the probabilities p per row. X<-matrix(rnorm(3*100),ncol=3) ## indicator matrix for missingnes (1 observed, 0 missing) R<-matrix(c(1,1,1, 0,0,1, 1,1,0, 0,1,1),ncol=3,byrow=TRUE) ## probabilities for row 1, row 2, row 3 and row 4

Hello all, A friend just showed me how ks.test fails to work with pbinom for small "size". Example: x<-rbinom(10000,10,0.5) x2<-rbinom(10000,10,0.5) ks.test(x,pbinom,10,0.5) ks.test(x,pbinom,size = 10, prob= 0.5) ks.test(x,x2) The tests gives significant p values, while the x did come from binom with size = 10 prob = 0.5. What test should I use instead ? Thanks, Tal

Hi, I am wondering if anyone can suggest how to test the equality of 2 proportions. The caveat here is that the 2 proportions were calculated from the same number of samples using 2 different tests. So essentially we are comparing 2 accuracy rates from same, say 100, samples. I think this is like a paired test, but don't know if really we need to consider the "paired" nature of the

Hello dear R help group, I have the following setup to analyse: We have about 150 subjects, and for each subject we performed a pair of tests (under different conditions) 18 times. The 18 different conditions of the test are complementary, in such a way so that if we where to average over the tests (for each subject), we would get no correlation between the tests (between subjects). What we wish

Dear list, I have data like this: dat1 <- data.frame(subject=rep(1:10,2), cond1=rep(c("A","B"),each=5), cond2=rep(c("C","D"),each=10), choice=sample(0:1,10,replace=TRUE)) I would like to compare subjects' "choice" for (cond1=="A" & cond2=="C") vs

Dear friends, If I have a table like this, first row A B C D ... are different levels of the variable, first column 0 1 2 4 ... are the levels of the "numbers", the numbers inside the table are the probabilities of the "number" occuring. A B C D ... 0 0.2 0.3 0.1 0.05 1 0.1 0.1 0.2 0.2 2 0.02 0.2 0 0.1 4 0.3 0.01 0.01

Hello dear R help group, I would like to download the tRNA data on: http://gtrnadb.ucsc.edu/download.html And then import it into R. Can anyone direct me as to how to do so? Thanks, Tal ---------------------------------------------- My contact information: Tal Galili E-mail: Tal.Galili@gmail.com Phone number: 972-52-7275845 FaceBook: Tal Galili My Blogs: http://www.talgalili.com (Web and

Could I have some suggestions as to how (various ways) I can display my confidence interval results? rm(list = ls()) set.seed(1) func <- function(d,t,beta,lambda,alpha,p.gamma,delta,B){ d <- c(5,1,5,14,3,19,1,1,4,22) t <- c(94.32,15.72,62.88,125.76,5.24,31.44,1.048,1.048,2.096,10.48) post <- matrix(0, nrow = 11, ncol = B) theta <- c(lambda,beta) beta.hat <- 2.471546 for(j

My question if in the Subject, but if to extend: I am specifically curious about WordPress blogs. But any solution will give me a lead. Thanks, Tal ---------------------------------------------- Contact me: Tal.Galili@gmail.com | 972-52-7275845 Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il (Hebrew) | www.r-statistics.com/ (English) [[alternative HTML version deleted]]

Hello dear R-help group. I wish to plot a scatter plot using icons (or images) instead of points. Is it possible? and how so? Thanks, Tal ---------------------------------------------- My contact information: Tal Galili E-mail: Tal.Galili@gmail.com Phone number: 972-52-7275845 FaceBook: Tal Galili My Blogs: http://www.talgalili.com (Web and general, Hebrew) http://www.biostatistics.co.il

Dear R fans, I am trying to do step-wise linear regression using the F-test to decide which variables to admit. Ewout Steyerberg suggests using the F-test for this purpose. I first build a model using no variables using lm(y ~ 1) and then using one variable that is a strong predictor using lm(y ~ x). When I call var.test on these two models, I do not get a significant p-value—0.07. But a

dear all, i'm trying to reproduce an spss-anova in R. It is an 2x3x3 repeated measures desingn with repeated contrasts. In R i've coded a contrast matrix for all factors and made a split in the aov summary - but I can't get the repeated interaction contrasts. The output from SPSS looks like this: TaskSw * CongNow * CongBefore: SS df Mean Square F Sig. 1 vs. 2 1 vs. 2 1 vs. 2

After reading more, I understand I didn't formulate my last question correctly, so please allow me to rephrase: What I am looking for is a way to save the R console session output. That is, a command that would combine the results of using: ?sink # And ?savehistory My motivation for this is that doing it will allow someone who is a blind user of R to be able to easily export his results to

I created a 2 D plan: > plot(range(-2.5,0.95),range(0.00,1.00),type="n",axes=TRUE) I made a projection of points with their coordonates (X,Y) in that plan > fullpoints=read.csv2("fullpoints.csv",h=T) > plot(fullpoints) The points are listed in that .csv file it is organized this way: 0,48875 0,142857143 0,409 0,142857143 0,45611 0,25 0,49833 0,222222222 0,61158

Hi dear R-help memebers, When building a CART model (specifically classification tree) using rpart, it is sometimes obvious that there are variables (X's) that are meaningful for predicting some of the outcome (y) variables - while other predictors are relevant for other outcome variables (y's only). *How can it be estimated, which explanatory variable is "used" for which of

Hi everybody, I would like to count how many times names in list L, nombreL, apear in list C, nombreC. Can I improve the next program? cuenta <- 0 topL <- length(nombreL) topC <- length(nombreC) for (i in 1:topL) { for (j in 1:topC) { k <- grep(noquote(nombreL[i]),nombreC[j])

Hello all, I would like to recreate the plot shown here (from a useR 2009 presentation): http://www.agrocampus-ouest.fr/math/useR-2009/abstracts/pdf/Hocking.pdf I downloaded the code for that image, and discovered that it relies on external web services, and also having PERL installed on the computer. I believe this could be done "locally" using the "seqLogo"

Hello all, I recently discovered the "comment" command. I see it can only hold a vector of characters. Is there a way (or an alternative), to make it possible to have it keep a list? (for example, to keep different pieces of information like date of creation, information of each variable and so on) The closest solution I can think of is using 'names' on the vector, like this: