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A Nonparametric Approach to Matched Pairs with Missing Data

Author

Listed:
  • MICHAEL G. AKRITAS

    (Pennsylvania State University)

  • JOUNI KUHA

    (London School of Economics)

  • D. WAYNE OSGOOD

    (Pennsylvania State University)

Abstract

The matched-pairs t-statistic on the overall ranks is extended to data with observations missing at random. Either one of the two variables is allowed to be missing. The procedure is completely nonparametric. Comparisons with the likelihood ratio test for normal data indicate that the proposed method fares well when the data are normal and outperforms it in other cases. Simulations also confirm that the proposed method has higher power than common nonparametric complete-pairs tests for observations missing completely at random. Finally, a data set on the delinquent values of boys released from correctional institutions is analyzed and discussed.

Suggested Citation

  • Michael G. Akritas & Jouni Kuha & D. Wayne Osgood, 2002. "A Nonparametric Approach to Matched Pairs with Missing Data," Sociological Methods & Research, , vol. 30(3), pages 425-454, February.
    • Handle: RePEc:sae:somere:v:30:y:2002:i:3:p:425-454
    DOI: 10.1177/0049124102030003006
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    References listed on IDEAS

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    1. U. Munzel, 1999. "Nonparametric methods for paired samples," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 53(3), pages 277-286, November.
    2. Akritas, Michael G., 1992. "Rank transform statistics with censored data," Statistics & Probability Letters, Elsevier, vol. 13(3), pages 209-221, February.
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    Cited by:

    1. Giovanni Di Franco, 2014. "An alternative procedure for imputing missing data based on principal components analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(3), pages 1149-1163, May.
    2. Hani M. Samawi & Robert Vogel, 2014. "Notes on two sample tests for partially correlated (paired) data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(1), pages 109-117, January.
    3. Konietschke, F. & Harrar, S.W. & Lange, K. & Brunner, E., 2012. "Ranking procedures for matched pairs with missing data — Asymptotic theory and a small sample approximation," Computational Statistics & Data Analysis, Elsevier, vol. 56(5), pages 1090-1102.

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