Multiple imputation refers to a set of stochastic imputation routines aimed at preserving the multivariate features of the data

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Is maximum likelihood a form of data substitution? Or not?

I’m using maximum likelihood with missing data. In this case of missing data, is maximum likelihood a form of data substitution? I’m significantly more familiar with multiple imputation which I ...
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5 views

Pooled results missing from GENLINMIXED multilevel analysis of multiple imputation data

I am running a multilevel analysis with the GENLINMIXED command (Analyze>Mixed Models>Generalized Linear Models) on a set of multiple imputation data. The data file was generated by the Multiple ...
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33 views

Multiple Imputation methods

Suppose that a variable $Y_j$ has missing values. We can use regression to impute the data using the nonmissing observations: $$Y_j = \beta_0+\beta_{1}Y_{1}+\beta_{2}Y_{2} + \dots + \beta_{(j-1)} ...
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19 views

Formula for pooling variance components across imputations in mixed effects models?

I've had no luck with this question. I see here that someone has asked a very good question about combining confidence intervals. I haven't been able to find anything about even combining the ...
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81 views

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 ...
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11 views

pooling the results from a repeated measures using multiple imputation

How can I pool the results from a multiply imputed repeated measures analysis? SPSS does not the pooling, as it does for other analysis types. From a technical standpoint, it is not at all clear. ...
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9 views

Multiple Imputation on SPSS number of parameters issue

I have to do several analysis on scores from questionnaires but unfortunately, I have some missing data and I was told that doing multiple imputation to replace them was the best solution. So far I ...
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1answer
22 views

multiple imputation models containing categorical variables

I have been using multiple imputation to estimate missing values in a single continuous exposure variable. One of the variables used in my imputation model is a categorical variable (occupation), with ...
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17 views

Sensitivity analysis for multiple imputation

I have developed a logistic regression model based on retrospective data from a national trauma database of head injury in the UK. The key outcome is 30 day mortality (denoted as ...
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23 views

Is regression dilution bias avoided by using time-dependent predictors?

Regression dilution bias implies that even random measurement errors may bias the results by pushing the regression slope towards zero. Cross-sectional studies are particularly susceptible to ...
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1answer
56 views

Multiple Imputation Using Amelia [duplicate]

I am using Amelia for multiple imputation, and I am satisfied with the imputed results. But I want to restrict the imputed variable to positive values. Is there a way that Amelia can handle it or ...
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30 views

How to impute cause of failure with mice?

In survival data, I have a variable cause of death, coded cause 1 and cause 2. Some of the patients are censored and the rest are dead from the cause 1 or 2. I have missing values on cause of death, ...
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17 views

Multiple Imputations: Do all variables need to be included, even if they are complete?

Let's say I have some variables with complete data, and some incomplete. In SPSS's MI add-on you can select some or all of the variables as the first step in the MI process (except subject ID). Does ...
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1answer
39 views

Multiple Imputation: If “Pooled” isn't “averaged” then what is it?

I used MI for a couple variables, and just want to be sure I know what SPSS did when it pooled test statistics. I've read that "pooled" is not "averaged"...so what is the calculation being done when ...
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61 views

Multiple imputation of conditional variables

I need to impute the missing values of a dataset of medical data in which several variables only make sense if another variable has a specific value. In the questionnaire the data come from they were ...
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18 views

Fit statistics and imputed data

I have a general question about pooling fit statistics when using multiple imputations. I am trying to pool the AIC, BIC, G-squared, or log likelihood across 10 imputed data sets. Is it possible to ...
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42 views

Multiply imputing data, but using just one of the imputed data sets

All, I have a question about what's practical when it comes to presenting results of multiply imputed data. I'm well-versed on the difference among MCAR/MAR/MNAR and approaches to imputing the data ...
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1answer
34 views

Something wrong with as.mids from mice package in R?

I am running some imputations using the mice package in R. During this process I need to use the as.mids function. However, it seems that as.mids change the values of my subsequent analysis - but I ...
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3answers
173 views

Smaller standard errors *after* multiple imputation?

I have 1771 observations, with 30% missing data for x1 (Yes:No), and no other missing values from 26 other variables (mix of continuous and factor). I am using quantile regression in R, with and ...
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1answer
46 views

multiple imputation of longitudinal, time-unstructured data

I have a longitudinal dataset of radiation exposures of an occupational cohort. A percentage of the exposure values are missing and I would like to multiply impute the missing values (it is one option ...
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95 views

Combining p-values from multiple imputed data sets

I have created a set of imputed data sets using 'mice'. The data is longitudinal in nature, with both a longitudinal outcome and survival outcome of interest, and time-varying predictors. I conducted ...
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1answer
30 views

Combine imputation and weighting in R

I'm dealing with stratified cluster sampling data. I would like to do multiple imputation first and then use weights in R. I looked at the survey-package for weighting and the mi- and mice-package for ...
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1answer
85 views

Data pre-processing: Multiple imputation

Q1: When using multiple imputation, a missing value is replaced by multiple estimated values at a time, thus creating multiple samples of the original one. If this is the case, should we run the ...
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35 views

Multiple Imputation and Matrix Completion

It is quite common that data sets will contain missing values in them. Suppose we want to try to fill in the missing values. For this we have techniques such as single/multiple imputation and matrix ...
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101 views

Multiple Imputation - Help Needed

These multiple imputation results relate to data I have previously described and shown here - Skewed Distributions for Logistic Regression Three variables I am using have missing data. Their names, ...
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2answers
57 views

Imputing using CFA for use in a Cox regression

I am using CFA (confirmatory factor analysis) to create a measurement model of social capital that is to be used in a Cox regression. Because of missing data I first impute the incomplete data by MICE ...
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93 views

Multiple imputation in SPSS: merge datasets?

I have two sets of data, measured from the same persons. The variables in the two sets are very different. There are some extreme values (occurring at random) in both sets I would like to handle using ...
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16 views

Multiple Imputation for Spatial Models

I'm trying to estimate various spatial models (SAR, SDM, SEM) but have missing data throughout my variables. The mice package in R gives a straightforward solution when none of the variables with a ...
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38 views

Non parametric test after multiple imputation

In advance, I'm not a statistician and I'm a SPSS user (although I also use STATA fairly well and R rarely). I'm having some trouble in making some nonparametric comparisons after Multiple ...
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66 views

R MICE imputation failing

I am really baffled about why my imputation is failing in R's Mice 2.22 package. I am attempting a very simple operation with the following data frame: ...
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35 views

Taking only a single data set from a multiple imputation?

If I use a package like R's mice to do multiple imputation, then only select the first of the resulting imputations and use that as a single imputation -- ignoring ...
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1answer
64 views

Linear Model or Time Series Model or ANOVA?

I have some data: column 1 = dates (daily data from say 1st Jan 2014 to 1 July 2014) column 2 = person (about 10 different people) column 3 = sales made (daily data from say 1st Jan 2014 to 1 ...
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56 views

Multiple imputation vs single imputation

We have missing data which we want to impute in order to provide an imputed value to some business users. However, we will not be providing any other information other than the point estimate. In ...
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1answer
50 views

Imputation of a binary variable by Bayesian logistic regression

In the book "Flexible Imputation of Missing Data" by Van Buuren, the following algorithm is presented I think I understand the algorithm as given, but I would like to know what is the "more ...
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154 views

Multiple Imputation and using Rubin's Rules on non-linear combination of estimates

When using multiple imputation, Rubin's rules can be used to pool the estimates. From my understanding though, the pooling should only be done on parameters that are asymptotically normal. What I ...
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383 views

Why is this multiple imputation low quality?

Consider the following R code: ...
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2answers
405 views

Is it possible to manually calculate standard deviation for a multiply-imputed survey variable based on the standard error (SE)?

I am analyzing a multiply-imputed complex sample survey data using Stata. For normally distributed numerical variables I want to report the mean and standard deviation. However, the Stata command for ...
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54 views

Degrees of freedom for a t-test using multiple imputation

I ran a paired samples t-test using multiple imputation in SPSS, and I am unsure as to how to proceed in reporting the degrees of freedom from the pooled data. The original data had 43 df and now it ...
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185 views

lmer with multiply imputed data

How can I get pooled random effects for lmer after multiple imputation? I am using mice to multiple impute a dataframe. And lme4 for a mixed model with random intercept and random slope. Pooling lmer ...
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1answer
394 views

Multiple imputation introduces negative values; dataset still valid?

After some detective work in my data sources, I realized the reasons for my previously reported 98% of missing data ratio. After implementing some data collection code fixes, the current missing data ...
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2answers
169 views

Error using mice() package in R for handling missing data [closed]

I am doing regression with a data with Y as target variable and 16 feature variables. I had two date feature variables which where as factor. I converted them to date format as shown below: ...
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25 views

Are pooled results from multiple imputation equivalent to a posterior mean?

I am fairly new to multiple imputation and trying to be sure I understand the approach. Say I have a data set with missing values, so I create 5 imputed data sets using multiple imputation by ...
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1answer
74 views

Is multiple imputation recommended to handle attrition?

I have PRE-POST data from a psychotherapy group intervention, including measures on anxiety, depression, QoL, coping, self-esteem, as well as demographic variables. I´m performing a t-test to examine ...
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36 views

Imputing values that depend on each other, such as percentiles or proportions

I have a data set with school level measures including test score percentiles. These percentiles are central to my analysis. For example, one measure is the test score of the 25th and 75th percentile ...
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1answer
111 views

Data imputation for meta analysis using mice package in R

I have a data-set with 32 effect size estimates- only 11 of which report a value for the continuous moderator of interest (the samples anxiety level). A complete case analysis (restricted to the 11 ...
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1answer
203 views

Pooling imputed, still not analysed datasets in MICE

I need to do a Multiple Imputation on a dataset with several missing values, and I need to do it with mice, because later I'll have to compare the results with those of imputations ran with other ...
3
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203 views

Negative imputed values

I am doing multiple imputation using chained equations in Stata to deal with item-missing data. One of the variables on which I did imputation was income. However after I did imputation, the imputed ...
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66 views

Multiple imputation to part of a dataset

I am working with a survey dataset which contains hundreds of variables. The item-missing data rate ranges from 0.2% to 10%. In order to retain study units with missing values and to maintain a ...
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37 views

multiple imputation for categorical data question

How do i design the use of Multiple Imputation based on Bayesian Inference when I am dealing with categorical data and my dataset does not contain complete prior observations at every combination ? ...
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47 views

multivariate dirichlet for multiple imputation

I dealing with 3 covariates {x1, x2, x3} all three are discrete and contain missing data. ...