similar to: Trouble with mChoice() in the Hmisc package.

Hi, I have a set of 30 binary variables measuring side effects after drug treatment. Since each subject can have multiple side effects, I want to display these side effects in a multiple choice table. I'm using the summary and mChoice functions of the Hmisc package, because it produces nicely formatted latex tables. My problem is, that table includes a category for people who have at

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.

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

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

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)

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Hmisc Version 3.3-2 has been posted to the CRAN repository. Change Log 3.3-2 4/26/2007 Fixed bug with combine<- function not handling NULL values. 3.3-1 3/29/2007 Created functions trunc.POSIXt, ceil.POSIXt, round.POSIXt to do those ops on POSIXt objects. Removed chron versions of these functions. Placed Hmisc in a namespace Factored out category

Hmisc Version 3.3-2 has been posted to the CRAN repository. Change Log 3.3-2 4/26/2007 Fixed bug with combine<- function not handling NULL values. 3.3-1 3/29/2007 Created functions trunc.POSIXt, ceil.POSIXt, round.POSIXt to do those ops on POSIXt objects. Removed chron versions of these functions. Placed Hmisc in a namespace Factored out category

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

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

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 =

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

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 =

Dear R users: Could you please help me out how to use R to get and interpret Standardized discriminant functions and structure coefficients for sex, Degree_Program, and Enrol_USM Please find the data file at: http://www.usm.maine.edu/~aaboueissa/Rhelps/Rhelps.html data files are (xls file: dataforRxls or txt file: dataforRtxt) Output looks like this table. Standardized

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")

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

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 >>>