similar to: About continuity correction option in the mantelhaen.test function.

Hi, I need to use the outputs from a complied program (*.exe program that is made by some one else) for numerous data sets and use R with the outputs for some computations. I thought that it would be very efficient if I can use R from the beginning to the end by calling the exe program and run it within R, continuing the computations based on the outputs. Are there any calling function for

Hello, I got the following message after fitting the poisson regression using the glm function. Are the results (coefficient estimates, their stderr, deviance, predicted values...) reliable? Can I still go on and interpret them? How much caution should I exercise for these results with this message? ########## > mmm6 <-glm(freq~x+y+x.2+y.2+x.3+y.3+x.4+y.4+x.5+y.5+x.6+y.6+xy

Just a general question concerning the woolf test (package vcd), when we have stratified data (2x2 tables) and when the p.value of the woolf-test is below 0.05 then we assume that there is a heterogeneity and a common odds ratio cannot be computed? Does this mean that we have to try to add more stratification variables (stratify more) to make the woolf-test p.value insignificant? Also in the

Hello, I am wondering if R has any ways to conduct the score test in logistic regression? Could you let me know please? Thanks, Insu -------------------------------------------------- This e-mail and any files transmitted with it may contain privileged or confidential information. It is solely for use by the individual for whom it is intended, even if addressed incorrectly. If you

Hi R users I have serveral binary variables (e.g., X1, X2, X3, X4, X5, X,6, and X7) and one continuous variable (e.g., Y1). I combined these variables using data.frame() mydata <- data.frame(X1,X2,X3,X4,X5,X6,X7,Y1) after that, I sorted this data.frame rank.by.Y1<-order(mydata[,8]) sorted.mydata<-mydata[rank.by.Y1,] after that, I replaced Y1's values with values ranging from 1

Full_Name: Chien-yu Peng Version: 2.0.1 OS: Windows XP Professional Submission from: (NULL) (140.109.72.181) Dear all: Although I don't know you, I am thankful for your help. When I use the function mantelhaen.test for R x C x K (R, C > 2) table, the output is not the same as SAS's. I don't know that the result consist with one of SAS's. But it works correctly for 2

Dear listers, I am trying to compute the exact conditional test given strata margins of a 2 by 2 by K array using the mantelhaen.test function to get a common odds ratio estimate. The estimate for the test on the following data is 0, which in my opinion dosen't make any sense. x <- array(c(53, 6098, 1006, 4521, 63, 8070, 1163, 6137), dim=c(2,2,2)) x , , 1 [,1] [,2] [1,] 53 1006

Hi, I am new to these functions. I'm wondering if there is anyway to save the entire results (all attributes of the result object) from the chisq.test or mantelhaen.test functions? For example, from chisq.test function, you will have statistic, parameter, p.value, expected, etc. in the result list. How can I save all of them in one shot to, says, a text file or csv file? Thank you. - adschai

Hi, My apologies for the naive question! I have three overlapping sets and I want to find the probability of finding a larger/greater intersection for 'A intersect B intersect C' (in the example below, I want to find the probability of finding more than 135 elements that are common in sets A, B & C). For a two set problem, I guess I would do a Fisher or chi-square test. Here is what

Hi, does anyone know of a function to calculate odds ratios in multiway tables (stratified) (+ the other usual statistics involved) i mean: say we have a table r*c*d, For every d (depth) we have a r*c table, and in this table the odds ratio's are calculated for every 2*2 subtable in it. logically this function would look like): ORs(multiwaytable) or ORs(data$var1r,data$var2c,data$var3d)

Estimado Oliver Nuñez Envío un ejemplo reproducible. Javier Marcuzzi # de donde tomo datos, y tiene el modelo (en el pdf) library(MCMCglmm) # librería con las funciónes que voy a usar library(nlme) datos0<-ChickWeight # creo algunos datos que agrego a los origonales Factor<-as.numeric(datos0$Chick) Factor[Factor > 0 & Factor <= 10] <- 'A' Factor[Factor > 10

I apologize in advance if this is the wrong forum for this report/request, and for the fact that I have not read the code for ftable.formula in any detail. >From reading the documentation for ftable.formula, I expected that the following two calls to ftable would produce the same results: data(UCBAdmissions) ftable(UCBAdmissions, row.vars = "Dept", col.vars = c("Gender",

Dear All, I'd like to perform the generalized Cochran-Mantel-Haenszel-Test (as described in Agresti (1990), Categorical Data Analysis) for my nominal data. My problem is that I have more than two groups. In fact I think I'd need an 5-dimensional array for the response variable, the control variable and three group variables. Could you please tell me if this is possible in R - and if

This is an OpenPGP/MIME signed message (RFC 2440 and 3156) --------------enig5A700CC15DEABD01445A1B70 Content-Type: text/plain; charset=ISO-8859-1 Content-Transfer-Encoding: quoted-printable Hi, I have modified the code originally posted to include capability for arbitrary weightings for the rows and columns (which apply in the nominal-ordinal and the ordinal-ordinal cases). The code is pasted

Suppose I have a table constructed from structable or simply just an object of class table. How can I convert it to a latex object? I looked in RSiteSearch, but only found info about matrices or data frames. Steve For example, here is a table t2 > str(t2) table [1:2, 1:2, 1:2] 6 8 594 592 57 ... - attr(*, "dimnames")=List of 3 ..$ Hospital : chr [1:2] "A"

I'm looking for an R method to produce latex versions of tables for table/array objects of 3 or more dimensions, which, of necessity is flattened to a 2D display, for example with ftable(), or vcd::structable, as shown below. I'd be happy to settle for a flexible solution for the 3D case. > UCB <- aperm(UCBAdmissions, c(2, 1, 3)) > ftable(UCB) Dept A B

Dear List, I'm having problem with an exercise from The R book (M.J. Crawley) on page 567. Here is the entire code upto the point where I get an error. data(UCBAdmissions) x <- aperm(UCBAdmissions, c(2, 1, 3)) names(dimnames(x)) <- c("Sex", "Admit?", "Department") ftable(x) fourfoldplot(x, margin = 2) dept<-gl(6,4) sex<-gl(2,1,24)

> addmargins(UCBAdmissions, FUN = list(Total=sum)) works with no problems, but consider: > myFUN <- list(Total=sum) > addmargins(UCBAdmissions, FUN = myFUN) Error in "names<-.default"(`*tmp*`, value = "") : names() applied to a non-vector Is this a bug? > R.version _ platform i386-pc-mingw32 arch i386 os mingw32 system

Hello, Currently it's possible to convert an object of class table to a data frame with as.data.frame.table(), but there's no ready-made function, AFAIK, to do the reverse operation, i.e. conversion of a data frame to a table. Do you think it would be a good idea to add a data.frame method to as.table(), to allow such conversions? The idea is that if `x' is a table and `y <-

I am fairly new to log-linear modelling, so as opposed to trying to fit modells, I am still trying to figure out how it actually works - hence I am looking at the interpretation of parameters. Now it seems most people skip this part and go directly to measuring model fit, so I am finding very few references to actual parameters, and am of course clear on the fact that their choice is irelevant for