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Increasing Power for Observational Studies of Aberrant Response: An Adaptive Approach

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arxiv 1907.06770 v3 pith:WMGZTNA2 submitted 2019-07-15 stat.ME

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keywords approachaberrantdevelopstudiestestadaptivemantel-haenszelobservational
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abstract

In many observational studies, the interest is in the effect of treatment on bad, aberrant outcomes rather than the average outcome. For such settings, the traditional approach is to define a dichotomous outcome indicating aberration from a continuous score and use the Mantel-Haenszel test with matched data. For example, studies of determinants of poor child growth use the World Health Organization's definition of child stunting being height-for-age z-score $\leq -2$. The traditional approach may lose power because it discards potentially useful information about the severity of aberration. We develop an adaptive approach that makes use of this information and asymptotically dominates the traditional approach. We develop our approach in two parts. First, we develop an aberrant rank approach in matched observational studies and prove a novel design sensitivity formula enabling its asymptotic comparison with the Mantel-Haenszel test under various settings. Second, we develop a new, general adaptive approach, the two-stage programming method, and use it to adaptively combine the aberrant rank test and the Mantel-Haenszel test. We apply our approach to a study of the effect of teenage pregnancy on stunting.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Gaussian comparison above the median

    math.ST 2026-07 accept novelty 7.0 of 10

    A centered Gaussian with smaller covariance assigns at least as much probability as one with larger covariance to any closed convex set with reference probability at least 1/2.

  2. Stochastic Sensitivity Analysis for Matched Observational Studies

    stat.ME 2026-06 unverdicted novelty 7.0 of 10

    Stochastic sensitivity analysis for matched studies finds worst-case conditional laws for hidden confounders instead of worst-case realizations, controlled by a sensitivity parameter that permits imperfect alignment w...

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