Testing weak nulls in matched observational studies
Author(s)
Fogarty, Colin B
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We develop sensitivity analyses for weak nulls in matched observational
studies while allowing unit-level treatment effects to vary. The methods may be
applied to studies using any optimal without-replacement matching algorithm. In
contrast to randomized experiments and to paired observational studies, we show
for general matched designs that over a large class of test statistics, any
valid sensitivity analysis for the entirety of the weak null must be
unnecessarily conservative if Fisher's sharp null of no treatment effect for
any individual also holds. We present a sensitivity analysis valid for the weak
null, and illustrate why it is generally conservative if the sharp null holds
through new connections to inverse probability weighted estimators. An
alternative procedure is presented that is asymptotically sharp if treatment
effects are constant, and that is valid for the weak null under additional
restrictions which may be deemed benign by practitioners. Simulations
demonstrate that this alternative procedure results in a valid sensitivity
analysis for the weak null hypothesis under a host of reasonable
data-generating processes. The procedures allow practitioners to assess
robustness of estimated sample average treatment effects to hidden bias while
allowing for unspecified effect heterogeneity in matched observational studies.
Date issued
2019-08-20Department
Massachusetts Institute of Technology. Operations Research CenterJournal
Biometrics
Publisher
Wiley
Citation
Fogarty, Colin B. 2019. "Testing weak nulls in matched observational studies." Biometrics.
Version: Final published version