Efficient ways to impute incomplete panel data

Kristian Kleinke; Mark Stemmler; Jost Reinecke; Friedrich Lösel

doi:10.1007/s10182-011-0179-9

Efficient ways to impute incomplete panel data

Kristian Kleinke, Mark Stemmler, Jost Reinecke, Friedrich Lösel

Human Development and Family Studies

Research output: Contribution to journal › Review article › peer-review

19 Scopus citations

Abstract

We find that existing multiple imputation procedures that are currently implemented in major statistical packages and that are available to the wide majority of data analysts are limited with regard to handling incomplete panel data. We review various missing data methods that we deem useful for the analysis of incomplete panel data and discuss, how some of the shortcomings of existing procedures can be overcome. In a simulation study based on real panel data, we illustrate these procedures' quality and outline fruitful avenues of future research.

Original language	English (US)
Pages (from-to)	351-373
Number of pages	23
Journal	AStA Advances in Statistical Analysis
Volume	95
Issue number	4
DOIs	https://doi.org/10.1007/s10182-011-0179-9
State	Published - Dec 2011

All Science Journal Classification (ASJC) codes

Analysis
Statistics and Probability
Modeling and Simulation
Social Sciences (miscellaneous)
Economics and Econometrics
Applied Mathematics

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10.1007/s10182-011-0179-9

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abstract = "We find that existing multiple imputation procedures that are currently implemented in major statistical packages and that are available to the wide majority of data analysts are limited with regard to handling incomplete panel data. We review various missing data methods that we deem useful for the analysis of incomplete panel data and discuss, how some of the shortcomings of existing procedures can be overcome. In a simulation study based on real panel data, we illustrate these procedures' quality and outline fruitful avenues of future research.",

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AU - Kleinke, Kristian

AU - Stemmler, Mark

AU - Reinecke, Jost

AU - Lösel, Friedrich

PY - 2011/12

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N2 - We find that existing multiple imputation procedures that are currently implemented in major statistical packages and that are available to the wide majority of data analysts are limited with regard to handling incomplete panel data. We review various missing data methods that we deem useful for the analysis of incomplete panel data and discuss, how some of the shortcomings of existing procedures can be overcome. In a simulation study based on real panel data, we illustrate these procedures' quality and outline fruitful avenues of future research.

AB - We find that existing multiple imputation procedures that are currently implemented in major statistical packages and that are available to the wide majority of data analysts are limited with regard to handling incomplete panel data. We review various missing data methods that we deem useful for the analysis of incomplete panel data and discuss, how some of the shortcomings of existing procedures can be overcome. In a simulation study based on real panel data, we illustrate these procedures' quality and outline fruitful avenues of future research.

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JO - AStA Advances in Statistical Analysis

JF - AStA Advances in Statistical Analysis

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Efficient ways to impute incomplete panel data

Abstract

All Science Journal Classification (ASJC) codes

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