Exact Confidence Limits on Some New Measures of Concordance and Discordance in Binary Outcomes.

Abstract:

:Using a measure of agreement that does not distinguish the "positive" outcome from the "negative" outcome can be sometimes misleading in assessing resemblance. To alleviate this concern, some new indices, including the "positive" and "negative" conditional synchrony measures (CSM) (or the conditional discordant measures [CDM]), as well as their related measures, have been recently proposed elsewhere. We show that one can easily derive exact confidence limits for these new indices. Using Monte Carlo simulation, we find that the asymptotic interval estimator derived from the score test and these exact interval estimators can all perform well in a variety of situations, while the asymptotic interval estimator based on Wald's statistic can lose accuracy. We use the data taken from a cross-sectional validation study assessing the diagnostic performance of the Whooley questions for major depression disorder (MDD) among older adults to illustrate the use of these interval estimators developed here.

journal_name

Ther Innov Regul Sci

authors

Lui KJ

doi

10.1007/s43441-019-00074-6

subject

Has Abstract

pub_date

2020-03-01 00:00:00

pages

437-443

issue

2

eissn

2168-4790

issn

2168-4804

pii

10.1007/s43441-019-00074-6

journal_volume

54

pub_type

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