Displaying 20 results from an estimated 188 matches for "imputation".

2008 Oct 29

1

Help with impute.knn

ear all,
This is my first time using this listserv and I am seeking help from the
expert. OK, here is my question, I am trying to use impute.knn function
in impute library and when I tested the sample code, I got the error as
followingt:
Here is the sample code:
library(impute)
data(khanmiss)
khan.expr <- khanmiss[-1, -(1:2)]
## ## First example
## if(exists(".Random.seed"))

2010 Aug 10

1

Multiple imputation, especially in rms/Hmisc packages

Hello, I have a general question about combining imputations as well as a
question specific to the rms and Hmisc packages.
The situation is multiple regression on a data set where multiple
imputation has been used to give M imputed data sets. I know how to get
the combined estimate of the covariance matrix of the estimated
coefficients (average the M covar...

2003 Jul 27

1

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 + signs],
n.impute=20, defaultLinear=T, data=t1)
# I read that 20 is better than the default of 5.
# defaultLinear makes sense for our data.
fmp <- fit.mult.impute(Y ~ X1 + X2 ... [for the model of inte...

2011 Mar 31

2

fit.mult.impute() in Hmisc

I tried multiple imputation with aregImpute() and
fit.mult.impute() in Hmisc 3.8-3 (June 2010) and R-2.12.1.
The warning message below suggests that summary(f) of
fit.mult.impute() would only use the last imputed data set.
Thus, the whole imputation process is ignored.
"Not using a Design fitting function; summary(fi...

2011 Dec 02

2

Imputing data

So I have a very big matrix of about 900 by 400 and there are a couple of NA
in the list. I have used the following functions to impute the missing data
data(pc)
pc.na<-pc
pc.roughfix <- na.roughfix(pc.na)
pc.narf <- randomForest(pc.na, na.action=na.roughfix)
yet it does not replace the NA in the list. Presently I want to replace the
NA with maybe the mean of the rows or columns or

2006 Sep 25

2

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:
- mean/median substitution
- substitution by a value selected from the observed values of a variable
- MLE in the mix package
- all available methods for numerical data...

2013 Jan 14

0

Changing MaxNWts with the mi() function (error message)

...ting the variable, "sex,"
the mi() function accesses the mi.categorical() function, which then
accesses the nnet() function. I then receive the following error
message (preceded by my code below):
> imputed.england=mi(england.pre.imputed, n.iter=6, add.noise=FALSE)
Beginning Multiple Imputation ( Mon Jan 14 13:39:49 2013 ):
Iteration 1
Chain 1 : sex
Error while imputing variable: sex , model: mi.categorical
Error in nnet.default(X, Y, w, mask = mask, size = 0, skip = TRUE,
softmax = TRUE, :
too many (3432) weights
The error message indicates that there are too many weights (3432)....

2011 Aug 01

1

Impact of multiple imputation on correlations

Dear all,
I have been attempting to use multiple imputation (MI) to handle missing data in my study. I use the mice package in R for this. The deeper I get into this process, the more I realize I first need to understand some basic concepts which I hope you can help me with.
For example, let us consider two arbitrary variables in my study that have the fol...

2003 Jul 25

1

Difficulty replacing NAs using Hmisc aregImpute and Impute

...aframe. I have
read the help pages and example in above sited pdf file, but to no avail.
Here is example of what I did.
Ph, my data frame, is attached.
> xt <- aregImpute (~ q5 + q22rev02 + q28a, n.impute=10, x=T, data=Ph)
Iteration:1 2 3 4 5 6 7 8 9 10 11 12 13
> impute(xt)
Multiple Imputation using Bootstrap and PMM
aregImpute(formula = ~q5 + q22rev02 + q28a, data = Ph, n.impute = 10,
x = T)
Method: ace n= 406 p= 3 Imputations: 10
Number of NAs:
q5 q22rev02 q28a
0 88 51
R-squares for Predicting Non-Missing Values for Each Variable
Using Last I...

2013 Feb 14

2

Plotting survival curves after multiple imputation

I am working with some survival data with missing values.
I am using the mice package to do multiple imputation.
I have found code in this thread which handles pooling of the MI results:
https://stat.ethz.ch/pipermail/r-help/2007-May/132180.html
Now I would like to plot a survival curve using the pooled results.
Here is a reproducible example:
require(survival)
require(mice)
set....

2003 Jun 16

1

Hmisc multiple imputation functions

Dear all;
I am trying to use HMISC imputation function to perform multiple imputations
on my data and I keep on getting errors for the code given in the help
files.
When using "aregImpute" the error is;
>f <- aregImpute(~y + x1 + x2 + x3, n.impute=100)
Loading required package: acepack
Iteration:1 Error in .Fortran("wc...

2005 May 26

1

PAN: Need Help for Multiple Imputation Package

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, â€œError: subscript out of
bounds....

2012 Oct 30

1

Amelia imputation - column grouping

Hi everybody,
I am quite new to data imputation, but I would like to use the R package '
Amelia II: A Program for Missing Data '. However, its unclear to me how
the input for amelia should look like:
I have a data frame consisting of numerous coulmns, which represent
different experimental conditions, whereby each column has 3 replicat...

2004 Sep 01

3

Imputing missing values

Dear all,
Apologies for this beginner's question. I have a
variable Price, which is associated with factors
Season and Crop, each of which have several levels.
The Price variable contains missing values (NA), which
I want to substitute by the mean of the remaining
(non-NA) Price values of the same Season-Crop
combination of levels.
Price Crop Season
10 Rice Summer
12

2011 Dec 13

0

snpStats imputed SNP probabilities

Hi,
Does anybody know how to obtain the imputed SNP genotype probabilities from the snpStats package?
I am interested in using an imputation method implemented in R to be further used in a simulation study context.
I have found the snpStats package that seems to contain suitable functions to do so.
As far as I could find out from the package vignette examples and its help, it gives the 'dosage' as the output which is the expec...

2011 Jan 31

2

Rubin's rules of multiple imputation

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.

2010 Jul 14

1

Changing model parameters in the mi package

...able needs a higher threshold than
1500. Is there a way that I can change the MaxNWts parameter that is
being sent to nnet.default()? I've investigated the mi() and
mi.info() functions and cannot see a way.
Thanks for your help! Error message and system info below:
Beginning Multiple Imputation ( Wed Jul 14 10:25:06 2010 ):
Iteration 1
Imputation 1 : min.func*
Error while imputing variable: min.func , model: mi.categorical
Error in nnet.default(X, Y, w, mask = mask, size = 0, skip = TRUE,
softmax = TRUE, :
too many (2608) weights
System is Mac OS X 10.5.8, R version 2.9.2
An...

2009 Apr 22

1

Multiple imputations : wicked dataset ? Wicked computers ? Am I cursed ? (or stupid ?)

Dear list,
I'd like to use multiple imputations to try and save a somewhat badly
mangled dataset (lousy data collection, worse than lousy monitoring, you
know that drill... especially when I am consulted for the first time
about one year *after* data collection).
My dataset has 231 observations of 53 variables, of which only a very
few has no...

2007 Jul 17

0

Multiple imputation with plausible values already in the data

...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 missing values properly, that is using
multiple imputation (with the mix package). But I am not sure how to do the
imputation, since the data set provided by the OECD already contains variables
with plausible values.
Roughly, the situation is like this: for each of the cognitive (achievement)
scales, there are five variables holding plausible values. So f...

2007 Sep 24

0

longitudinal imputation with PAN

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 and I have i...