search for: buuren

...57:05 +0100 Hi, it is impossible to plot a subset of the variables at the moment, but we could add it. p.s. The latest version of mice is v1.14, which can be downloaded from CRAN. Roel de Jong. Leo G?rtler wrote: > Hello... > > how can I plot mice.mids objects as described by Buuren (2000) > http://web.inter.nl.net/users/S.van.Buuren/mi/docs/Manual.pdf > page 17, if there are many variables (~80) with NAs included? > mice runs well, but the plot is not possible because it seems that there > are too many variables. > > > imp.temp <- mice(data.withn...

Hi I am trying to impute missing values for my data.frame. As I intend to use the complete data for prediction I am currently measuring the success of an imputation method by its resulting classification error in my training data. I have tried several approaches to replace missing values: - mean/median substitution - substitution by a value selected from the observed values of a variable - MLE

R-helpers: I have a dataset that has 168 subjects and 12 variables. Some of the variables have missing data and I want to use the multiple imputation capabilities of the "mice" package to address the missing data. Given that mice only supports linear models and generalized linear models (via the lm.mids and glm.mids functions) and that I need to fit Cox models, I followed the previous

Hi I have downloaded a FLAC file somewhere and when trying to decode it to WAV it gives the error message: ERROR, MD5 signature mismatch So my question is now: are FLAC files that give the error message above still decodable to WAV (and how can you do this, because flac.exe doesn't want to decode the file), even if there is a MD5 signature mismatch, or is this not possible at all? thx

...to bypass problems caused by perfect prediction.Special attention to transformations, sum scores, indices and interactions using passive imputation, and to the proper setup of the predictor matrix. We have written also a complete new manual for mice, which can be downloaded from http://www.stefvanbuuren.nl/publications/MICE%20in%20R%20-%20Draft.pdf <https://webmail.kpnplanet.nl/exchweb/bin/redir.asp?URL=http://www.stefvanbuuren.nl/publications/MICE%2520in%2520R%2520-%2520Draft.pdf> This article/manual provides a hands-on, stepwise approach to using mice for solving incomplete data problems...

...to bypass problems caused by perfect prediction.Special attention to transformations, sum scores, indices and interactions using passive imputation, and to the proper setup of the predictor matrix. We have written also a complete new manual for mice, which can be downloaded from http://www.stefvanbuuren.nl/publications/MICE%20in%20R%20-%20Draft.pdf <https://webmail.kpnplanet.nl/exchweb/bin/redir.asp?URL=http://www.stefvanbuuren.nl/publications/MICE%2520in%2520R%2520-%2520Draft.pdf> This article/manual provides a hands-on, stepwise approach to using mice for solving incomplete data problems...

Hi Folks, I don't often grumble, but this time I've found myself inconvenienced by a posting stored on R-help archives: https://stat.ethz.ch/pipermail/r-help/2009-September/211095.html This was Karin Groothuis-Oudshoorn & Stef van Buuren's message on 10 September about the new version of MICE. This has been sent by software which inserted no line-breaks. As a result, each paragraph is viewed (by my browser, Firefox) as one very long line, not wrapped. In particular, the third paragraph, about the extensions which have been int...

I am using -mice- for multiple imputation and would like to use the gelman diagnostic in -coda- to assess the convergence of my imputations. However, gelman.diag requires an mcmc list as input. van Buuren and Groothuis-Oudshoorn (2011) recommend running mice step-by-step to assess convergence (e.g. imp2 <- mice.mids(imp1, maxit = 3, print = FALSE) ) but this creates mids objects. How can I convert the mids objects into an mcmc list? Or is the step-by-step approach wrong here? thanks, Rachel...

Hello, I have climatic data of various years with many missing values. I would like to know what tools in R are most suited to estimate this missing values. (New in R and quite new on statistics). Thanks, G

Dear R users, I've used the function qr.fit.sfn to estimate a quantile regression on a panel data set. Now I would like to compute an statistic to measure the goodness of fit of this model. Does someone know how could I do that? I could compute a pseudo R2 but in order to do that I would need the value of the objetive function at the optimum and I don't see how to get this from the

I'd like to search the r-help archives. Is there a way? I want to find out how to impute missing values. -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To:

Hi Folks, I'm currently looking at missing data/imputation methods (including multiple imputation). S-Plus has a "missing data library". What similar resources are available within R? Or does one roll one's own? Best wishes to all, Ted. -------------------------------------------------------------------- E-Mail: (Ted Harding) <Ted.Harding at nessie.mcc.ac.uk>

...048 > Note : various repeats crashed at various points (one of tre trials started to simulate, and stopped at obs 177...), but the numerical accuracy seemed involved every time. The "textbook example" (example for amelia function) runs perfectly. Package "mice" (Stef van Buuren & Karin Groothuis-Oudshoorn) : > system.time(DataTest.mice<-mice(DataTest,m=5)) iter imp variable 1 1 cadredpErreur dans mice.impute.logreg(c(1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, : dims [produit 28] ne correspond pas ? la longueur de l'objet [31] De plus : Warning messa...

CRAN (and crantastic) updates this week New packages ------------ * disclapmix (0.1) Maintainer: Mikkel Meyer Andersen Author(s): Mikkel Meyer Andersen and Poul Svante Eriksen License: GPL-2 http://crantastic.org/packages/disclapmix disclapmix makes inference in a mixture of Discrete Laplace distributions using the EM algorithm. * EstSimPDMP (1.1) Maintainer: Unknown Author(s):

...to bypass problems caused by perfect prediction.Special attention to transformations, sum scores, indices and interactions using passive imputation, and to the proper setup of the predictor matrix. We have written also a complete new manual for mice, which can be downloaded from http://www.stefvanbuuren.nl/publications/MICE%20in%20R%20-%20Draft.pdf <https://webmail.kpnplanet.nl/exchweb/bin/redir.asp?URL=http://www.stefvanbuuren.nl/publications/MICE%2520in%2520R%2520-%2520Draft.pdf> This article/manual provides a hands-on, stepwise approach to using mice for solving incomplete data problems...