Does more accurate exposure prediction necessarily improve health effect estimates?

Szpiro, AA; Paciorek, CJ; Sheppard, L

HERO ID

759873

Reference Type

Journal Article

Year

2011

Language

English

PMID

21716114

HERO ID 759873
In Press No
Year 2011
Title Does more accurate exposure prediction necessarily improve health effect estimates?
Authors Szpiro, AA; Paciorek, CJ; Sheppard, L
Journal Epidemiology
Volume 22
Issue 5
Page Numbers 680-685
Abstract A unique challenge in air pollution cohort studies and similar applications in environmental epidemiology is that exposure is not measured directly at subjects' locations. Instead, pollution data from monitoring stations at some distance from the study subjects are used to predict exposures, and these predicted exposures are used to estimate the health effect parameter of interest. It is usually assumed that minimizing the error in predicting the true exposure will improve health effect estimation. We show in a simulation study that this is not always the case. We interpret our results in light of recently developed statistical theory for measurement error, and we discuss implications for the design and analysis of epidemiologic research.
Doi 10.1097/EDE.0b013e3182254cc6
Pmid 21716114
Wosid WOS:000293447500013
Is Certified Translation No
Dupe Override No
Is Public No
Language Text English
Is Peer Review No
Is Qa No
Relationship(s)