BOOK-CHAPTER

Bias Reduction Using Mahalanobis-Metric Matching

Donald B. Rubin

Year: 2006 Cambridge University Press eBooks Pages: 160-166   Publisher: Cambridge University Press

Abstract

: Monte Carlo methods are used to study the ability of nearest-available, Mahalanobis-metric matching to make the means of matching variables more similar in matched samples than in random samples.

Keywords:
Mahalanobis distance Metric (unit) Matching (statistics) Reduction (mathematics) Artificial intelligence Mathematics Computer science Pattern recognition (psychology) Statistics Engineering Geometry Operations management

Metrics

5
Cited By
0.00
FWCI (Field Weighted Citation Impact)
0
Refs
0.05
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Face and Expression Recognition
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Spectroscopy and Chemometric Analyses
Physical Sciences →  Chemistry →  Analytical Chemistry
Gene expression and cancer classification
Life Sciences →  Biochemistry, Genetics and Molecular Biology →  Molecular Biology

Related Documents

JOURNAL ARTICLE

Bias Reduction Using Mahalanobis-Metric Matching

Donald B. Rubin

Journal:   Biometrics Year: 1980 Vol: 36 (2)Pages: 293-293
JOURNAL ARTICLE

BIAS REDUCTION USING MAHALANOBIS METRIC MATCHING

Donald B. Rubin

Journal:   ETS Research Bulletin Series Year: 1978 Vol: 1978 (2)
JOURNAL ARTICLE

Corrections: Correction to 'Bias Reduction Using Mahalanobis-Metric Matching'

Journal:   Biometrics Year: 1980 Vol: 36 (4)Pages: 752-752
© 2026 ScienceGate Book Chapters — All rights reserved.