Displaying 20 results from an estimated 2000 matches similar to: "Multiple Imputation in mice/norm"
2009 Jul 17
3
Package norm has been removed. What to use for Maximum Likelihood Missing Data Imputation?
Hello,
I apologize if an answer to my questions is available, or if I
submitted this question incorrectly. I have read the mailing lists, as
well as the R Project and CRAN homepages. However, I may have missed
something.
I noticed the package 'norm' has been removed. Its page
http://cran.r-project.org/web/packages/norm/index.html now reads:
"Package ?norm? was removed from the CRAN
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.
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
2011 Oct 18
1
getting basic descriptive stats off multiple imputation data
Hi, all,
I'm running multiple imputation to handle missing data and I'm running into a problem. I can generate the MI data sets in both amelia and the mi package (they look fine), but I can't figure out how to get pooled results. The examples from the mi package, zelig, etc., all seem to go right to something like a regression, though all I want are the mean and SE for all the
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 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).
2011 Jul 25
0
Debugging multiple imputation in mice
Hello all,
I am trying to impute some missing data using the mice package. The data
set I am working with contains 125 variables (190 observations),
involving both categorical and continuous data. Some of these variables
are missing up to 30% of their data.
I am running into a peculiar problem which is illustrated by the
following example showing both the original data (blue) and the imputed
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
2011 Jul 20
1
Calculating mean from wit mice (multiple imputation)
Hi all,
How can I calculate the mean from several imputed data sets with the package
mice?
I know you can estimate regression parameters with, for example, lm and
subsequently pool those parameters to get a point estimate using functions
included in mice. But if I want to calculate the mean value of a variable
over my multiple imputed data sets with
fit <- with(data=imp, expr=mean(y)) and
2012 Dec 08
1
imputation in mice
Hello! If I understand this listserve correctly, I can email this address
to get help when I am struggling with code. If this is inaccurate, please
let me know, and I will unsubscribe.
I have been struggling with the same error message for a while, and I can't
seem to get past it.
Here is the issue:
I am using a data set that uses -1:-9 to indicate various kinds of missing
data. I changed
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
2012 Oct 19
0
impute multilevel data in MICE
Dear list,
Is there any one use MICE package deal with multilevel missing values here? I have a question about the 2lonly.pmm() and 2lonly.norm(), I get the following error quite often. Here is the code the error, could you give me some advice please? Am I using it in the right way?
> ini=mice(bhrm,maxit=0)
> pred=ini$pred
> pred
V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15
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
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
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
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
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
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