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  4. Excess relative risk as an effect measure in case-control studies of rare diseases
 
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Excess relative risk as an effect measure in case-control studies of rare diseases

Journal
PLoS ONE
Journal Volume
10
Journal Issue
4
Date Issued
2015
Author(s)
WEN-CHUNG LEE  
DOI
10.1371/journal.pone.0121141
URI
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84928682538&doi=10.1371%2fjournal.pone.0121141&partnerID=40&md5=2c77b0aaf890cfef7a3ead51a52cb460
https://scholars.lib.ntu.edu.tw/handle/123456789/521801
Abstract
Epidemiologists often use ratio-type indices (rate ratio, risk ratio and odds ratio) to quantify the association between exposure and disease. By comparison, less attention has been paid to effect measures on a difference scale (excess rate or excess risk). The excess relative risk (ERR) used primarily by radiation epidemiologists is of peculiar interest here, in that it involves both difference and ratio operations. The ERR index (but not the difference-type indices) is estimable in case-control studies. Using the theory of sufficient component cause model, the author shows that when there is no mechanistic interaction (no synergism in the sufficient cause sense) between the exposure under study and the stratifying variable, the ERR index (but not the ratio-type indices) in a rare-disease case-control setting should remain constant across strata and can therefore be regarded as a common effect parameter. By exploiting this homogeneity property, the related attributable fraction indices can also be estimated with greater precision. The author demonstrates the methodology (SAS codes provided) using a case-control dataset, and shows that ERR preserves the logical properties of the ratio-type indices. In light of the many desirable properties of the ERR index, the author advocates its use as an effect measure in case-control studies of rare diseases. ? 2015 Wen-Chung Lee.
SDGs

[SDGs]SDG3

Other Subjects
adult; Article; attributable fraction among the exposed population; case control study; controlled study; disease association; effect measure; excess relative risk; exposure; heart infarction; human; mathematical analysis; measurement accuracy; middle aged; oral contraceptive use; population attributable fraction; population risk; rare disease; ratio type index; risk; statistical analysis; procedures; Rare Diseases; risk assessment; risk factor; statistical model; Case-Control Studies; Humans; Models, Statistical; Rare Diseases; Risk Assessment; Risk Factors
Publisher
Public Library of Science
Type
journal article

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