Missing data imputation, matching and other applications of random recursive partitioning

DOI10.1016/J.CSDA.2006.12.036zbMath1452.62075OpenAlexW2079229132MaRDI QIDQ1020880

Giuseppe Porro, Stefano Maria Iacus

Publication date: 2 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2006.12.036

zbMATH Keywords

classificationrecursive partitioningmissing data imputationaverage treatment effect estimation

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Computational methods for problems pertaining to statistics (62-08) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Missing data (62D10)

Related Items (6)

Recursive partitioning for missing data imputation in the presence of interaction effects ⋮ Distance functions for matching in small samples ⋮ Comparison of alternative imputation methods for ordinal data ⋮ Preserving the distribution function in surveys in case of imputation for zero inflated data ⋮ Editorial: Special issue on statistical algorithms and software ⋮ Incremental tree-based missing data imputation with lexicographic ordering

Uses Software

• R
• MASS (R)
• LIBSVM

Cites Work

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• Does matching overcome LaLonde's critique of nonexperimental estimators?
• Practical propensity score matching: a reply to Smith and Todd
• Rejoinder: ``Does matching overcome LaLonde's critique of nonexperimental estimators?
• Nearest-neighbor classification with categorical variables.
• Statistical Analysis of Financial Data in S-Plus
• Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme
• Characterizing Selection Bias Using Experimental Data
• Random forests
• Observational studies.

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