Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Questions tagged [mice]

MICE is an R package which implements Multivariate Imputation by Chained Equations using Fully Conditional Specification

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How do the number of imputations & the maximum iterations affect accuracy in multiple imputation?

The help page for MICE defines the function as: mice(data, m = 5, method = vector("character", length = ncol(data)), predictorMatrix = (1 - diag(1, ncol(data))), visitSequence = (1:ncol(data))[apply(is.na(data), 2, any)], form =…
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"the leading minor of order 1 is not positive definite" error using 2l.norm in mice

I am having a problem using the 2l.norm method of multilevel imputation in mice. Unfortunately I cannot post a reproducible example because of the size of my data - when I reduce the size, the problem vanishes. For a particular variable, mice…
Robert Long
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How does the mice imputation function work?

I was wondering if anyone had experience using the mice function, as described in mice: Multivariate Imputation by Chained Equations in R (JSS 2011 45(3))? I have a dataset with a number of variables, each with varying degrees of missing data. My…
mjburns
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How to improve running time for R MICE data imputation

My question in short: are there methods to improve on the running time of R MICE (data imputation)? I'm working with a data set (30 variables, 1.3 million rows) which contains (quite randomly) missing data. About 8% of the observations in about 15…
Dendrobates
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Diagnosing why MICE is crashing R when attempting to impute multilevel data

I have never had problems with R crashing before. I am using the mice package (mice 2.13) to perform multiple imputations. The code works fine on some subsets of the data, but when I run it on other subsets, R crashes (not immediately - after some…
Robert Long
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How to pool results from post hoc lsmeans analysis across multiple imputations with MICE

I have five imputed datasets created with MICE in R, and am running run some post hoc analyses using the lsmeans package. Although MICE has great functions to easily pool and compare models (e.g. pool() and pool.compare()), they won't work…
jaminday
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How to combine/pool binomial confidence intervals after multiple imputation?

After I multiply imputed my dataset m times I wanted to calculate a binomial proportion confidence interval. How I can I combine the various estimates of the confidence intervals while taking Rubins rules into account?
sluijs
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Questions on multiple imputation with MICE for a multigroup-SEM-analysis? (including survey weights)

I am planning to do a multigroup SEM analysis. I gathered survey data and calculated a survey weight. Some of my variables have item nonresponse (mostly around 5% missings). I´ve decided to use multiple imputation to handle the missing data. First,…
SEMson
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Bootstrapped confidence intervals for the parameters of a linear model applied to multiply imputed data

I would like to construct CIs for $\beta$ in the linear model $Y = X\beta + \epsilon$ I observe $\{X', Y'\}$ which is $\{X,Y\}$ contaminated with values missing at random. $\epsilon$ is not Gaussian and not homoscedastic. I propose to construct CIs…
orizon
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Why does MICE fail to impute multilevel data with 2l.norm and 2l.pan?

Why does MICE fail to impute multilevel data with 2l.norm and 2l.pan in this situation ? Here is a reproducible example: require(foreign) require(mice) require(pan) dt.fail <- read.csv("http://goo.gl/pg8um") dt.fail$X <- NULL dt.fail$out <-…
Robert Long
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perform Random Forest AFTER multiple imputation with MICE

i wanted to build a prediction model. Since my data had some missing data, I imputed data with the MICE algorithm. After that I wanted to do a regression with Random Forest. Now I'm kinda stuck because: I wanted to do Multiple Imputation with MICE…
ching
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Sensitivity Analysis for Missing Not at Random (MNAR) data

I currently have a dataset which contains variables with different degrees of missingingness. One of the key variables for my analysis has about 12% of the values Missing Not at Random (MNAR). From previous research I have done, I gather that most…
RNB
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compute 95% confidence interval for predictions using a pooled model after multiple imputation?

I am conducting multiple imputation by chained equations in R using the MICE package, followed by a logistic regression on the imputed dataset. I need to compute a 95% confidence interval about the predictions for use in creating a plot—that is, the…
user5280725
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Do I need to adjust the degrees of freedom returned by pool.compare() in MICE?

I am analyzing a multiply imputed dataset produced from the MICE package in R. To assess the overall significance of my linear model, I am using pool.compare() to compare my "full" model to an intercept only "restricted" model. However, the degrees…
MattStatsNeale
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Visualising plausible values in multiple imputation

I have been checking density plots to get a feel for the plausibility of values that have been imputed using the mice package in R. I would be grateful for some advice/guidance/comment on the following problem. The imputations are created by a call…
Joe King
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