similar to: NA's in multiple choice summary table in Hmisc

Dear all, With the latest update of Hmisc I no longer have any problems with latex. However using the ctable option produces latex code that at least on both the miktex distribution at work and mactex distribution at home refuses to run due to an extra blank line inserted between the multicolumn lines in the latex code... It runs fine if the line is deleted or if the ctable option is left out.

Hi All:-- I've started using the the Hmisc reporting facilities recently, mostly successfully. I'm having some trouble with mChoice() multiple-choice objects, though. Here's some example code and output from R-help a couple of years ago: library(Hmisc) Symptom1 <- c("Headache", "Headache", NA) Symptom2 <- c(NA, "Anxiety", NA) Symptoms <-

Dear all, I did post this more or less identical mail in a follow up to another question I posted, but under another heading. I try again, but now under the correct header. upon running this code (from the Hmisc library-latex function) I believe the call to summary.formula is allright and produces wonderful tables, but the latex command results in a correct formatted table but where all the

Un texte encapsul? et encod? dans un jeu de caract?res inconnu a ?t? nettoy?... Nom : non disponible URL : <https://stat.ethz.ch/pipermail/r-help/attachments/20080725/bcafe250/attachment.pl>

I have data on a number of patients. Essentially, for each patient I know his/her age and whether he/she exhibits certain symptoms: age symptom1 symptom2 50 0 1 53 0 0 70 1 1 ... I have started off by fitting simple models with forms like Prob(patient of age t shows symptom i) = 1 - Exp(-lambda_i * t) or Prob(patient of age t shows

In the Hmisc package there is a new data class 'mChoice' for multiple choice variables. There are format and as.numeric methods (the latter creates a matrix of dummy variables). mChoice variables are not allowed by model.frame. Is there a way to specify a conversion function that model.frame will use automatically? I would use as.factor here. model.frame does not seem to use

In the Hmisc package there is a new data class 'mChoice' for multiple choice variables. There are format and as.numeric methods (the latter creates a matrix of dummy variables). mChoice variables are not allowed by model.frame. Is there a way to specify a conversion function that model.frame will use automatically? I would use as.factor here. model.frame does not seem to use

Hello, I finally run my measurement model in sem - successfully. Now, I am trying to print out the path diagram that is based on the results - but for some reason it's not working. Below is my script - but the problem is probably in my very last line: # ANALYSIS OF ANXIETY, DEPRESSION, AND FEAR - LISREL P.31 library(sem) # Creating the ANXIETY, DEPRESSION, AND FEAR intercorrelation matrix

I am new to R. I just tried to recreate in R (using sem package and the identical input data) a solution for a simple measurment model I have found before in LISREL. LISREL had no problems and converged in just 3 iterations. In sem, I got no solution, just the warning message: "Could not compute QR decomposition of Hessian. Optimization probably did not converge. in: sem.default(ram =

I am having two problems creating data frames that I have solutions, but they really seem like kludges and I assume I just don't understand the proper R way of doing things. The first situation is I have an set of uneven data vectors. When I try to use them to create a data frame I would like the bottoms of them padded with NAs, without explicitly specifying that. When I do: anxiety.data =

On Fri, 19 Jun 2020 14:46:19 +0000 "Keane, Erich via llvm-dev" <llvm-dev at lists.llvm.org> wrote: > If the name of our branch causes anxiety/difficulty for a significant > portion of our population, it is literally the least we can do to > choose a word that better respects the last few centuries of world > history. Honestly, if the name of a branch causes

Hi all, I have received the following error from summary.manova: Error in summary.manova(manova.test, test = "Pillai") : residuals have rank 36 < 64 The data is simulated data for 64 variables. The design is a 2*2 factorial with 10 replicates per treatment. Looking at the code for summary.manova, the error involves a problem with qr(). Does anyone have a suggestion as to how to

On 2020-06-19, Justin Hibbits via llvm-dev wrote: >On Fri, 19 Jun 2020 17:38:02 +0100 >Renato Golin <rengolin at gmail.com> wrote: > >> On Fri, 19 Jun 2020 at 16:43, Robinson, Paul via llvm-dev >> <llvm-dev at lists.llvm.org> wrote: >> > If anyone's keeping track of the voting: >> > +1 for "dev" (contrasts with "release")

Dear all, I?m trying to get a output table for age and the summary of a and b, stratified by epo as follows using summary.formula h<-data.frame(a=sample(c("A",NA),100,replace=T),b=sample(c("B",NA),100,replace=T),age=rnorm(100,50,25),epo=sample(c("Y","N"),100,T)) library(rms)

Hi all, I am trying to get a handle on gls (package nlme). I have a toy problem: 3 fixed factors (A, B, C), two levels each, 5 replicates per treatment. The response variable is continuous, normal. I have a correlation matrix of the form: > mat A B C A 1.00 0.75 0 B 0.75 1.00 0 C 0.00 0.00 1 which is common to all observations. How do I construct the call to gls? I think I need to

On Sat, Apr 19, 2014 at 05:42:12PM +0200, Patrik Horník wrote: > > Please confirm that this is fully correct solution (for my purpose, not > elegant clean way for official fix) and it has no negative consequences. It > seems that way but I did not analyze all code paths the fixed code is in. Yes, that's a fine solution. What I'll probably do is disable the check if

Hello, I need to plot multiple confidence intervals for the same model parameter e.g. so for the same value of the parameter in point x_1 I would like to see four different confidence intervals so that I can compare the accuracy e.g. boot basic vs normal vs my own vs classic lm CI etc. I like very very much the plotCI implemented here: http://cran.r-project.org/web/packages/plotrix/index.html

The irr package seems to install correctly: > install.packages("irr") trying URL 'http://cran.us.r-project.org/src/contrib/irr_0.61.tar.gz' Content type 'application/x-tar' length 13848 bytes opened URL ================================================== downloaded 13Kb * Installing *source* package 'irr' ... ** R ** data ** help >>>

I'm using read.delim to successfully read in tab delimited data, but some columns' values are comma seperated, reflecting the fact that user chose a few answers on a multi-select question. I understand that each answer is its own category and so could be represented as a seperate column in the data set, but I'd like the option of reading in the data column, and converting it to a

Dear R experts, I'm beginner. My question about ANOVA for unequal sample sized data should be obsolete but I can not clarify it. I have a dataset from 23 males and 18 females. I measured one condition('cond') with 4 levels. So I'd like to see main effect of gender, cond and gender by cond interaction and also postHoc test. (In fact, I have to do anova 90 times) * 1. Question