A signed-rank test for clustered data.

Abstract:

:We consider the problem of comparing two outcome measures when the pairs are clustered. Using the general principle of within-cluster resampling, we obtain a novel signed-rank test for clustered paired data. We show by a simple informative cluster size simulation model that only our test maintains the correct size under a null hypothesis of marginal symmetry compared to four other existing signed rank tests; further, our test has adequate power when cluster size is noninformative. In general, cluster size is informative if the distribution of pair-wise differences within a cluster depends on the cluster size. An application of our method to testing radiation toxicity trend is presented.

journal_name

Biometrics

journal_title

Biometrics

authors

Datta S,Satten GA

doi

10.1111/j.1541-0420.2007.00923.x

subject

Has Abstract

pub_date

2008-06-01 00:00:00

pages

501-7

issue

2

eissn

0006-341X

issn

1541-0420

pii

BIOM923

journal_volume

64

pub_type

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