similar to: Search for a usable pan manual

I'm looking for a port of Schafer's PAN module for multiple imputation of nested data. It is written in S-Plus, and I would like to use it in R. Any pointers most appreciated. Best wishes, Paul von Hippel

Dear all! I'd like to do multiple imputation of missing values with s-plus libraries that are provided by Shafer (http://www.stat.psu.edu/~jls/misoftwa.html). I wonder, whether these libraries are compatible or somehow convertible to R (because I don't have S-plus), so that I can use this functions using the R Program. I would be happy if you could tell me, -if it is possible to use

Hello all. I am trying to run PAN, multilevel multiple imputation program, in R to impute missing data in a longitudinal dataset. I could successfully run the multiple imputation when I only imputed one variable. However, when I tried to impute a time-varying covariate as well as a response variable, I received an error message, “Error: subscript out of bounds.” Can anyone tell if my commands

What R functionnalities are there to do missing values imputation (substantial proportion of missing data)? I would prefer to use maximum likelihood methods ; is the EM algorithm implemented? in which package? Thanks Anne ---------------------------------------------------- Anne Piotet Tel: +41 79 359 83 32 (mobile) Email: anne.piotet@m-td.com

Hi, I have a big dataset which has many missing values and want to implement Multiple imputation via Monte carlo markov chain by following J Schafer's "Analysis of incomplete multivariate data". I don't know where to begin and is looking for a sample R code that implements multiple imputation with EM, MCMC, etc.... Any help / suggestion will be greatly appreciated. David

Hi, Evgenia and I have copied an updated version of the mlbench package to CRAN which contains several new data sets. We have also changed some of the variable names to avoid name conflicts. Best, -- ------------------------------------------------------------------- Friedrich Leisch Institut f?r Statistik Tel: (+43 1) 58801 10715 Technische

Hi, Evgenia and I have copied an updated version of the mlbench package to CRAN which contains several new data sets. We have also changed some of the variable names to avoid name conflicts. Best, -- ------------------------------------------------------------------- Friedrich Leisch Institut f?r Statistik Tel: (+43 1) 58801 10715 Technische

I'm discovering R (very impressive), and didn't find in the docs a simple method for replacing, in a data frame, missing values (NA) with the column's mean (or any other method for reconstructing missing values when needed). Thanks in advance for your help. -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Hi all, I'm currently working with a dataset that has quite a few missing values and after some investigation I figured that multiple imputation is probably the best solution to handle the missing data in my case. I found several references to functions in S-Plus that perform multiple imputation (NORM, CAT, MIX, PAN). Does R have corresponding functions? I searched the archives but was not

Greetings folks, Shafer's S-plus package "norm" for multiple imputation of missing values in multivariate normal data has been most kindly and usefully ported to R by Alvaro A. Novo. Shafer's website http://www.stat.psu.edu/~jls/ lists four S-plus packages in all: NORM - multiple imputation of multivariate continuous data CAT - multiple imputation of multivariate

Hello all, if I have multiple imputed data sets, is there a command or function in R in any package you know of to combine those, I know one common MI approach is rubins rules, is there a way to do this using his rules or others? I know theres ways, like using Amelia from Gary King's website to create the imputed data sets, but how to make them into one or combine them for analysis.

Hi, I have had a quick search to see whether this question has been asked/answered before but haven't found anything directly related to it. Basically, I am wondering if I can run the packages, developed by Shafer for S-Plus, that allow multiple imputation of missing data - NORM, CAT, MIX, and PAN. If not, does anyone know if someone has done the modification that would make these packages

I am looking for a book that discusses the theory of multiple imputation (and other methods of dealing with missing data) and, just as importantly, how to implement these methods in R or S-Plus. Ideally, the book would have a structure similar to Faraway (Regression), Pinheiro&Bates (Mixed Effects) and Wood (GAMs) and would be very modern (i.e. published within the last couple of years).

Does anyone know if the pan news reader works on CentOS 5.4? I am considering installing version 0.132 that I downloaded from pan.rebelbase.com . Thanks for your advice. Mike.

Hi everyone, I'm analysing a survival analysis data set at the moment with missing values in the covariate and survival vectors (I have about 60 variables). I know there are some functions on the CRAN network to deal with missing values in general multivariate data. Does anybody know of any package that deals with missing data specifically in the context of survival analysis. Any help

I've run this test on every permutation of poll and notify: can NOT reproduce the crash: --with-ioloop=select --with-notify=none --with-ioloop=select --with-notify=dnotify --with-ioloop=select --with-notify=inotify --with-ioloop=poll --with-notify=none --with-ioloop=poll --with-notify=dnotify --with-ioloop=poll --with-notify=inotify CAN reproduce the crash: --with-ioloop=epoll

I realize this is (mostly) off topic, but I'm befuddled as to *how* one can post to the Gmane Pan Users' group (gmane.comp.gnome.apps.pan.user) using any nntp USENET client (e.g., Pan, on Centos). I'm already subscribed (by having sent an email to pan-users at nongnu.org); but I just want that USENET group to work like *this* USENET group, where I can post using a server:port

Dear R-List, I apologize for not posting a reproducible example - the reason is that I actually do not succeed in reproducing my specific problem with generated data. Let me still describe the problem: I want to impute missing data using the "pan" package. a) It works, when I use a fraction of my data (e.g. 200 out of 44000 cases) b) It works, when I generate a dataset of equal

Hello all, I am working on a longitudinal study of children in the UK and trying the PAN package for imputation of missing data, since it fulfils the critical criteria of taking into account individual subject trend over time as well as population trend over time. In order to validate the procedure I have started by deleting some known values ?we have 6 annual measures of height on 300 children

In testing the migration from courier-imap to dovecot I've discovered that the forward flag on messages isn't kept track of in a standard way. courier-imap seems to keep track of forwarded messages in courierimapkeywords/:list dovecot seems to add an 'a' flag to the filename. Unfortunately this 'a' flag information doesn't seem to be given out by dovecot. It's