[R] Multiple imputation with plausible values already in the data

Hello, this is not really an R-related question, but since the posting guide does not forbid asking non-R questions (even encourages it to some degree), I though I'd give it a try. I am currently doing some secondary analyses of the PISA (http://pisa.oecd.org) student data. I would like to treat

Re: [R] Multiple Imputation / Non Parametric Models / Combining Results

At 08:12 08/12/2006, Simon P. Kempf wrote: Dear R-Users, The following question is more of general nature than a merely technical one. Nevertheless I hope someone get me some answers. I am in no sense an expert in this area but since it seems that noone else has answered so far; I wonder

[R] Multiple Imputation / Non Parametric Models / Combining Results

Dear R-Users, The following question is more of general nature than a merely technical one. Nevertheless I hope someone get me some answers. I have been using the mice package to perform the multiple imputations. So far, everything works fine with the standard regressions analysis.

[R] multiple imputation

Hi, is it correct that multiple-Imputation like mice http://www.imputation.com can't understand as a standard data-mining task, beacuse i haven't a generalization mechanism perform the model on complete new and bigger dataset with a predict method!? many thanks regards, christian

Re: [R] multiple imputation

[EMAIL PROTECTED] wrote: Hi, is it correct that multiple-Imputation like mice http://www.imputation.com can't understand as a standard data-mining task, beacuse i haven't a generalization mechanism perform the model on complete new and bigger dataset with a predict method!? many

[R] Multiple imputation using mice with mean

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: -

Re: [R] Multiple imputation using mice with mean

On 25-Sep-06 Eleni Rapsomaniki wrote: 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

[R] multiple imputation of anova tables

Dear list members, how can multiple imputation realized for anova tables in R? Concretely, how to combine F-values and R^2, R^2_adjusted from multiple imputations in R? Of course, the point estimates can be averaged, but how to get standarderrors for F-values/R^2 etc. in R? For linear models,

Re: [R] multiple imputation with fit.mult.impute in Hmisc

Thanks for the quick reply! One more question, below. On 07/27/03 22:20, Frank E Harrell Jr wrote: On Sun, 27 Jul 2003 14:47:30 -0400 Jonathan Baron [EMAIL PROTECTED] wrote: I have always avoided missing data by keeping my distance from the real world. But I have a student who is doing a

Re: [R] multiple imputation with fit.mult.impute in Hmisc

On Mon, 28 Jul 2003 08:18:09 -0400 Jonathan Baron [EMAIL PROTECTED] wrote: Thanks for the quick reply! One more question, below. On 07/27/03 22:20, Frank E Harrell Jr wrote: On Sun, 27 Jul 2003 14:47:30 -0400 Jonathan Baron [EMAIL PROTECTED] wrote: I have always avoided missing data by

[R] multiple imputation with fit.mult.impute in Hmisc

I have always avoided missing data by keeping my distance from the real world. But I have a student who is doing a study of real patients. We're trying to test regression models using multiple imputation. We did the following (roughly): f - aregImpute(~ [list of 32 variables, separated by +

Re: [R] multiple imputation with fit.mult.impute in Hmisc

On Sun, 27 Jul 2003 14:47:30 -0400 Jonathan Baron [EMAIL PROTECTED] wrote: I have always avoided missing data by keeping my distance from the real world. But I have a student who is doing a study of real patients. We're trying to test regression models using multiple imputation. We did the

[R] Multiple imputation

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

RE: [R] Multiple imputation

-Original Message- From: Jonck van der Kogel [mailto:[EMAIL PROTECTED] Sent: Friday, 13 June 2003 7:58 AM To: [EMAIL PROTECTED] Subject: [R] Multiple imputation Hi all, I'm currently working with a dataset that has quite a few missing values and after some investigation I

Re: [R] Multiple imputation

On Thu, 12 Jun 2003 23:57:45 +0200 Jonck van der Kogel [EMAIL PROTECTED] wrote: 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

Re: [R] Multiple imputation

Dear Jonck, In addition, there are ports of both norm and mix in the contributed-packages section of CRAN. Regards, John At 07:48 PM 6/12/2003 -0400, Frank E Harrell Jr wrote: On Thu, 12 Jun 2003 23:57:45 +0200 Jonck van der Kogel [EMAIL PROTECTED] wrote: Hi all, I'm currently working with a