Displaying 20 results from an estimated 1000 matches similar to: "transcan() from Hmisc package for imputing data"
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("wclosepw", as.double(w), as.double(x),
2004 Nov 30
2
impute missing values in correlated variables: transcan?
I would like to impute missing data in a set of correlated
variables (columns of a matrix). It looks like transcan() from
Hmisc is roughly what I want. It says, "transcan automatically
transforms continuous and categorical variables to have maximum
correlation with the best linear combination of the other
variables." And, "By default, transcan imputes NAs with "best
2005 May 04
3
Imputation
I have timeseries data for some factors, and some missing values are there in those factors, I want impute those missing values without disturbing the distribution of that factor, and maintaining the correlation with other factors. Pl. suggest me some imputation methods.
I tried some functions in R like aregImpute, transcan. After the imputation I am unable to retrive the data with imputed
2007 Sep 26
1
using transcan for imputation, categorical variable
Dear all,
I am using transcan to impute missing values (single imputation). I have
several dichotomous variables in my dataset, but when I try to impute
the missings sometimes values are imputed that were originally not in
the dataset. So, a variable with 2 values (severe weight loss or
no/limited weight loss) for example coded 0 and 1, shows 3 different
values after imputation (0, 1 and 2).
I
2008 Jun 30
3
Is there a good package for multiple imputation of missing values in R?
I'm looking for a package that has a start-of-the-art method of
imputation of missing values in a data frame with both continuous and
factor columns.
I've found transcan() in 'Hmisc', which appears to be possibly suited
to my needs, but I haven't been able to figure out how to get a new
data frame with the imputed values replaced (I don't have Herrell's book).
Any
2006 Mar 24
0
Imputing NAs using transcan(); impute()
Dear all,
I'm trying to impute NAs by conditional medians using transcan() in
conjunction with impute.transcan().
... see and run attached example..
Everything works fine, however impute() returns saying
Under WINDOWS
> x.imputed <- impute(trans)
Fehler in assign(nam, v, where = where.out) :
unbenutzte(s) Argument(e) (where ...)
Zus?tzlich: Warnmeldung:
variable X1 does not
2012 Jul 05
0
Confused about multiple imputation with rms or Hmisc packages
Hello,
I'm working on a Cox Proportional Hazards model for a cancer data set that has missing values for the categorical variable "Grade" in less than 10% of the observations. I'm not a statistician, but based on my readings of Frank Harrell's book it seems to be a candidate for using multiple imputation technique(s). I understand the concepts behind imputation, but using
2008 Nov 26
1
multiple imputation with fit.mult.impute in Hmisc - how to replace NA with imputed value?
I am doing multiple imputation with Hmisc, and
can't figure out how to replace the NA values with
the imputed values.
Here's a general ourline of the process:
> set.seed(23)
> library("mice")
> library("Hmisc")
> library("Design")
> d <- read.table("DailyDataRaw_01.txt",header=T)
> length(d);length(d[,1])
[1] 43
[1] 2666
2005 Jul 09
1
aregImpute: beginner's question
Hello R-help,
Thanks for everyone's very helpful suggestions so far. I am now trying to
use aregImpute for my missing data imputation. Here are the code and error
messages. Any suggestions would be very much appreciated.
Sincerely,
Anders Corr
########################################
#Question for R-Help on aregImpute
########################################
#DOWNLOAD DATA (61Kb)
2007 Jun 22
1
Imputing missing values in time series
Folks,
This must be a rather common problem with real life time series data
but I don't see anything in the archive about how to deal with it. I
have a time series of natural gas prices by flow date. Since gas is not
traded on weekends and holidays, I have a lot of missing values,
FDate Price
11/1/2006 6.28
11/2/2006 6.58
11/3/2006 6.586
11/4/2006 6.716
11/5/2006 NA
11/6/2006 NA
11/7/2006
2005 Jul 08
2
missing data imputation
Dear R-help,
I am trying to impute missing data for the first time using R. The norm
package seems to work for me, but the missing values that it returns seem
odd at times -- for example it returns negative values for a variable that
should only be positive. Does this matter in data analysis, and/or is
there a way to limit the imputed values to be within the minimum and
maximum of the actual
2005 Jan 17
1
merge data frames taking mean/mode of multiple macthes
Hello :)
I have two data frames, one has properties taken on a
piece by piece basis and the other has performance on
a lot by lot basis. I wish to combine these two data
frames but the problem is that each lot has multiple
pieces and hence i need to take a mean of the
properties of multiple pieces and match it to the row
having data about the lot.
I was wondering if there is a simple commmand,
2003 Jul 25
1
Difficulty replacing NAs using Hmisc aregImpute and Impute
Hello R experts
I am using Hmisc aregImpute and Impute (following example on page 105 of The
Hmisc and Design Libraries).
*My end goal is to have NAs physically replaced in my dataframe. 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,
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(fit)
will use standard errors, t, P from last imputation only.
Use
2005 Aug 29
1
staying with R, jobs in R
Hi:
I started using R and am an avid fan of the product and also the concept. I
am considering switching jobs but do wish to continute with R while the
industry standard seems to be SAS. Is there any web site which posts jobs at
places which use R for their work.
avneet
--
An eye for an eye makes the whole world blind.
~Mahatma Gandhi
http://truthloveandcompassion.blogspot.com/
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
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 covariance matrices from the individual
2005 Apr 24
2
missing values
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
2010 Nov 01
1
Error message in fit.mult.impute (Hmisc package)
Hello,
I would like to use the aregImpute and fit.mult.impute to impute missing
values for my dataset and then conduct logistic regression analyses on the
data, taking into account that we imputed values. I have no problems
imputing the values using aregImpute, but I am getting an error at the
fit.mult.impute stage.
Here is some sample code (I actually have more observations and variables to
2005 Jan 19
1
Imputation missing observations
>From Internet I downloaded the file Hmisc.zip and used it for R package updation. and R gave the message 'Hmisc' successfull unpacked.
But when I use the functions like aregImpute the package is displaying coundn't find the function
Where as in help.search it is giving that use of the function
>