Displaying 20 results from an estimated 5000 matches similar to: "getting basic descriptive stats off multiple imputation data"
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.
2012 Jun 03
1
Multiple imputation, multinomial response & random effects
Dear R-group,
Could somebody recommend a package that can deal with a multinomial response variable (choice of breeding tactic in mice, which has four unordered levels), multiply-imputed data (generated using the Amelia package) and two non-nested random effects: individual identity (133 individuals made up to four choices each) and year (for which there are six levels and sample size varies
2010 Dec 22
3
Help with Amelia
Hi
I have used the amelia command from the Amelia R package. this gives me a number
of imputed datasets.
This may be a silly question, but i am not a statistician, but I am not sure how
to combine these results to obtain the imputed dataset to usse for further
statistical analysis. I have looked through the amelia and zelig manuals but
still can not find the answer. This maybe because I dont
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
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 replicates. I
want amelia to perform an imputation across
2012 Aug 20
1
Combining imputed datasets for analysis using Factor Analysis
Dear R users and developers,
I have a dataset containing 34 variables measured in a survey, which has
some missing items. I would like to conduct a factor analysis of this
data. I tested mi, Amelia, and MissForest as alternative packages in
order to impute the missing data. I now have 5 separate datasets with
the variables I am interested in factor analysing. In my reading of the
package
2011 Jul 14
1
Amelia_Multiple_Imputation_with_observational_priors_noms
I am fairly new at using R/programming in general so I apologize if I am
leaving crucial parts of the puzzle out, but here goes.
First and foremost this is the error I am receiving:
Error in muPriors[priors[, 1:2]] <- priors[, 3] :
NAs are not allowed in subscripted assignments
This occurs only when I am using observational priors and some number of
nominal variables, it does not
2009 Apr 24
1
Multiple Imputation in mice/norm
I'm trying to use either mice or norm to perform multiple imputation to fill
in some missing values in my data. The data has some missing values because
of a chemical detection limit (so they are left censored). I'd like to use
MI because I have several variables that are highly correlated. In SAS's
proc MI, there is an option with which you can limit the imputed values that
are
2008 Nov 04
2
ordered logistic regression of survey data with missing variables
Hello:
I am working with a stratified survey dataset with sampling weights
and I want to use multiple imputation to help with missingness.
1. Is there a way to run an ordered logistic regression using both a
multiply imputed dataset (i.e. from mice) and adjust for the survey
characteristics using the weight variable? The Zelig package is able
to do binary logistic regressions for survey
2012 Jan 13
2
Averaging over data sets
Hi all,
after using Amelia II to create 10 imputed data sets I need to average them
to have one unique data that includes the average for each cell of the
variables imputed, in addition to the values for the variables not imputed.
Such data has many variables (some numeric, other factors), and more than
20000 observations. I do not know how to average them out. Any help?
Below I provide a small
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 missing data. Most variables have 5-10% of
2007 Jun 07
1
MITOOLS: Error in eval(expr, envir, enclos) : invalid 'envir' argument
R-users & helpers:
I am using Amelia, mitools and cmprsk to fit cumulative incidence curves
to multiply imputed datasets. The error message that I get
"Error in eval(expr, envir, enclos) : invalid 'envir' argument"
occurs when I try to fit models to the 50 imputed datasets using the
"with.imputationList" function of mitools. The problem seems to occur
2010 Jun 30
3
Logistic regression with multiple imputation
Hi,
I am a long time SPSS user but new to R, so please bear with me if my
questions seem to be too basic for you guys.
I am trying to figure out how to analyze survey data using logistic
regression with multiple imputation.
I have a survey data of about 200,000 cases and I am trying to predict the
odds ratio of a dependent variable using 6 categorical independent variables
(dummy-coded).
2012 Jul 21
2
EM for missing data
Hi list,
I am wondering if there is a way to use EM algorithm to handle missing data and get a completed data set in R?
I usually do it in SPSS because EM in SPSS kind of "fill in" the estimated value for the missing data, and then the completed dataset can be saved and used for further analysis. But I have not found a way to get the a completed data set like this in R or SAS. With
2012 Jul 21
2
combined EM dataset for missing data?
Hi list,
I am wondering if there is a way to use EM algorithm to handle missing data and get a completed data set in R?
I usually do it in SPSS because EM in SPSS kind of "fill in" the estimated value for the missing data, and then the completed dataset can be saved and used for further analysis. But I have not found a way to get the a completed data set like this in R or SAS. With
2012 Oct 26
0
combined output with zelig is not working!?!
Hi everyone,
I have carried out a multiple imputation in R using Amelia II and have
created 5 multiply imputed datasets. The purpose of my research is to fit a
Poisson Model to the data to estimate numbers of hospital admissions.
Now that I have 5 completed datasets and I have to pool all the 5 datasets
to get one combined output for a poisson model.
I have checked previous queries about
2024 Jan 06
0
Amelia. Imputation of time-series data
Colleagues,
I have started working with Amelia, with the aim of imputing missing data for time-series data.
Although I have succeeded in getting Amelia to perform the imputation, I have not found any documentation describing how Amelia imputes time-series data. I have read the basic Amelia documentation, but it does not address how time-series data are imputed. The documentation describes
2013 Jan 07
1
Amelia algorithm
Dear all.
First of all, my english isn't verry good, but I hope I can convey my concern.
I've a general question about the Amelia algorithm. I'm no mathematician or
statistician, but I had to use R and impute and analyse some data, and Amelia
showed results that fitted my expectations. I'll have to defend my choice soon,
but I haven't totally grasped what Amelia does. I'm
2012 Dec 11
1
Debian packaging and openblas related crash when profiling in R
Hello R-sig-debian and (hopefully) Dirk:
On Debian wheezy, I have the R packaging that CRAN (you) provide. I
run into a little trouble while trying to fiddle with alternative
BLAS.
I know you and I went around on this last year and I think perhaps
I've found something wrong in the framework, or I've just done
something wrong.
I installed the packages openblas-base and openblas-dev, and
2004 Mar 23
0
New R package
Zelig: Everyone's Statistical Software
Kosuke Imai, Gary King and Olivia Lau
Version 1.0
(Available at http://gking.harvard.edu/zelig)
A growing proportion of statisticians and methodologists from many
disciplines are converging on R, a powerful statistics package and
programming language. As an open source project, R is freely