Saved in:
Bibliographic Details
Main Authors: Howard, Steven R., Pimentel, Samuel D.
Format: Preprint
Published: 2019
Subjects:
Online Access:https://arxiv.org/abs/1904.08895
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866910552808226816
author Howard, Steven R.
Pimentel, Samuel D.
author_facet Howard, Steven R.
Pimentel, Samuel D.
contents A sensitivity analysis in an observational study tests whether the qualitative conclusions of an analysis would change if we were to allow for the possibility of limited bias due to confounding. The design sensitivity of a hypothesis test quantifies the asymptotic performance of the test in a sensitivity analysis against a particular alternative. We propose a new, non-asymptotic, distribution-free test, the uniform general signed rank test, for observational studies with paired data, and examine its performance under Rosenbaum's sensitivity analysis model. Our test can be viewed as adaptively choosing from among a large underlying family of signed rank tests, and we show that the uniform test achieves design sensitivity equal to the maximum design sensitivity over the underlying family of signed rank tests. Our test thus achieves superior, and sometimes infinite, design sensitivity, indicating it will perform well in sensitivity analyses on large samples. We support this conclusion with simulations and a data example, showing that the advantages of our test extend to moderate sample sizes as well.
format Preprint
id arxiv_https___arxiv_org_abs_1904_08895
institution arXiv
publishDate 2019
record_format arxiv
spellingShingle The uniform general signed rank test and its design sensitivity
Howard, Steven R.
Pimentel, Samuel D.
Methodology
A sensitivity analysis in an observational study tests whether the qualitative conclusions of an analysis would change if we were to allow for the possibility of limited bias due to confounding. The design sensitivity of a hypothesis test quantifies the asymptotic performance of the test in a sensitivity analysis against a particular alternative. We propose a new, non-asymptotic, distribution-free test, the uniform general signed rank test, for observational studies with paired data, and examine its performance under Rosenbaum's sensitivity analysis model. Our test can be viewed as adaptively choosing from among a large underlying family of signed rank tests, and we show that the uniform test achieves design sensitivity equal to the maximum design sensitivity over the underlying family of signed rank tests. Our test thus achieves superior, and sometimes infinite, design sensitivity, indicating it will perform well in sensitivity analyses on large samples. We support this conclusion with simulations and a data example, showing that the advantages of our test extend to moderate sample sizes as well.
title The uniform general signed rank test and its design sensitivity
topic Methodology
url https://arxiv.org/abs/1904.08895