Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2018 Feb;67(2):307-327.
doi: 10.1111/rssc.12229. Epub 2017 Jun 15.

Survival analysis with functions of mismeasured covariate histories: the case of chronic air pollution exposure in relation to mortality in the nurses' health study

Xiaomei Liao  1   2 , Xin Zhou  1   2 , Molin Wang  1   2   3 , Jaime E Hart  4   3 , Francine Laden  2   4   3 , Donna Spiegelman  1   2   3   5   6
Affiliations

Survival analysis with functions of mismeasured covariate histories: the case of chronic air pollution exposure in relation to mortality in the nurses' health study

Xiaomei Liao et al. J R Stat Soc Ser C Appl Stat. 2018 Feb.

Abstract

Environmental epidemiologists are often interested in estimating the effect of functions of time-varying exposure histories, such as the 12-month moving average, in relation to chronic disease incidence or mortality. The individual exposure measurements that comprise such an exposure history are usually mis-measured, at least moderately, and, often, more substantially. To obtain unbiased estimates of Cox model hazard ratios for these complex mis-measured exposure functions, an extended risk set regression calibration method for Cox models is developed and applied to a study of long-term exposure to the fine particulate matter (PM2.5) component of air pollution in relation to all-cause mortality in the Nurses' Health Study. Simulation studies under several realistic assumptions about the measurement error model and about the correlation structure of the repeated exposure measurements were conducted to assess the finite sample properties of this new method, and found that the method has good performance in terms of finite sample bias reduction and nominal confidence interval coverage.

Keywords: Cox proportional hazards model; Functions of time-varying exposure histories; Measurement error; Risk set regression calibration.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Plot for relative bias in relation to the validation study size for AR(1) covariance structure, β1 = 0.5.
Figure 2
Figure 2
Normality plots for the residuals from the measurement error model (13). Left: Risk set 1; Right: Risk set 2.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Atkinson RW, Kang S, Anderson HR, Mills IC, Walton HA. Epidemiological time series studies of PM2.5 and daily mortality and hospital admissions: a systematic review and meta-analysis. Thorax. 2014;69:660–665. - PMC - PubMed
    1. Atkinson RW, Mills IC, Walton HA, Anderson HR. Fine particle components and health – a systematic review and meta-analysis of epidemiological time series studies of daily mortality and hospital admissions. J Expos Sci Environ Epidemiol. 2015;25:208–214. URL: http://dx.doi.org/10.1038/jes.2014.63. - DOI - PMC - PubMed
    1. Brook RD, Franklin B, Cascio W, Hong Y, Howard G, Lipsett M, Luepker R, Mittleman M, Samet J, Smith SCJ, Tager I. Air pollution and cardiovascular disease: a statement for healthcare professionals from the expert panel on population and prevention science of the american heart association. Circulation. 2004;109:2655–2671. - PubMed
    1. Carroll RJ, Ruppert D, Stefanski LA, Crainiceanu CM. Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition. Chapman and Hall; 2006.
    1. Chiuve SE, Rexrode KM, Spiegelman D, Logroscino G, Manson JE, Rimm EB. Primary prevention of stroke by healthy lifestyle. Circulation. 2008;118:947–54. - PMC - PubMed

Publication types

LinkOut - more resources