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Balancing and Elimination of Nuisance Variables

Author

Listed:
  • Noorbaloochi Siamak

    (Minneapolis VA Medical Center and University of Minnesota)

  • Nelson David

    (Minneapolis VA Medical Center and University of Minnesota)

  • Asgharian Masoud

    (McGill University)

Abstract

Addressing covariate imbalance in causal analysis will be reformulated as an elimination of the nuisance variables problem. We show, within a counterfactual balanced setting, how averaging, conditioning, and marginalization techniques can be used to reduce bias due to a possibly large number of imbalanced baseline confounders. The notions of X-sufficient and X-ancillary quantities are discussed and, as an example, we show how sliced inverse regression and related methods from regression theory that estimate a basis for a central sufficient subspace provide alternative summaries to propensity based analysis. Examples for exponential families and elliptically symmetric families of distributions are provided.

Suggested Citation

  • Noorbaloochi Siamak & Nelson David & Asgharian Masoud, 2010. "Balancing and Elimination of Nuisance Variables," The International Journal of Biostatistics, De Gruyter, vol. 6(2), pages 1-22, February.
  • Handle: RePEc:bpj:ijbist:v:6:y:2010:i:2:n:6
    DOI: 10.2202/1557-4679.1209
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    References listed on IDEAS

    as
    1. Noorbaloochi, Siamak & Nelson, David, 2008. "Conditionally specified models and dimension reduction in the exponential families," Journal of Multivariate Analysis, Elsevier, vol. 99(8), pages 1574-1589, September.
    2. Cook, R. Dennis & Forzani, Liliana, 2009. "Likelihood-Based Sufficient Dimension Reduction," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 197-208.
    3. Weisberg, Sanford, 2002. "Dimension Reduction Regression in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 7(i01).
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    Cited by:

    1. Nelson, David & Noorbaloochi, Siamak, 2013. "Information preserving sufficient summaries for dimension reduction," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 347-358.
    2. Yatracos, Yannis G., 2015. "Balancing scores for simultaneous comparisons of multiple treatments," Statistics & Probability Letters, Elsevier, vol. 107(C), pages 178-182.

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