A review of methods for misclassified categorical data in epidemiology.

Abstract:

:Misclassification introduces errors in categorical variables. This paper presents a review of methods for misclassified categorical data in epidemiology. Different sampling schemes for a 2 x 2 x 2 table and methods of analyses will be discussed first. A misclassification matrix is defined, and the usual misclassification models will be shown to be a subclass of log-linear models. Well-known results on a 2 x 2 table with misclassification and recent results on a 2 x 2 x 2 table are then reviewed. Finally two methods of adjusting for misclassification will be given. The first method assumes a known misclassification matrix, and the second method uses subsampling to estimate the misclassification matrix. The analysis is based on a recursive system of log-linear models: first determine a misclassification model, then select a model for the correctly classified variables. The methods are illustrated by data from traffic safety research on the effectiveness of seatbelt use in reducing injuries.

journal_name

Stat Med

journal_title

Statistics in medicine

authors

Chen TT

doi

10.1002/sim.4780080908

subject

Has Abstract

pub_date

1989-09-01 00:00:00

pages

1095-106; discussion 1107-8

issue

9

eissn

0277-6715

issn

1097-0258

journal_volume

8

pub_type

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