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June 2015 Biased sampling designs to improve research efficiency: Factors influencing pulmonary function over time in children with asthma
Jonathan S. Schildcrout, Paul J. Rathouz, Leila R. Zelnick, Shawn P. Garbett, Patrick J. Heagerty
Ann. Appl. Stat. 9(2): 731-753 (June 2015). DOI: 10.1214/15-AOAS826


Substudies of the Childhood Asthma Management Program [ Control. Clin. Trials 20 (1999) 91–120; N. Engl. J. Med. 343 (2000) 1054–1063] seek to identify patient characteristics associated with asthma symptoms and lung function. To determine if genetic measures are associated with trajectories of lung function as measured by forced vital capacity (FVC), children in the primary cohort study retrospectively had candidate loci evaluated. Given participant burden and constraints on financial resources, it is often desirable to target a subsample for ascertainment of costly measures. Methods that can leverage the longitudinal outcome on the full cohort to selectively measure informative individuals have been promising, but have been restricted in their use to analysis of the targeted subsample. In this paper we detail two multiple imputation analysis strategies that exploit outcome and partially observed covariate data on the nonsampled subjects, and we characterize alternative design and analysis combinations that could be used for future studies of pulmonary function and other outcomes. Candidate predictor (e.g., IL10 cytokine polymorphisms) associations obtained from targeted sampling designs can be estimated with very high efficiency compared to standard designs. Further, even though multiple imputation can dramatically improve estimation efficiency for covariates available on all subjects (e.g., gender and baseline age), relatively modest efficiency gains were observed in parameters associated with predictors that are exclusive to the targeted sample. Our results suggest that future studies of longitudinal trajectories can be efficiently conducted by use of outcome-dependent designs and associated full cohort analysis.


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Jonathan S. Schildcrout. Paul J. Rathouz. Leila R. Zelnick. Shawn P. Garbett. Patrick J. Heagerty. "Biased sampling designs to improve research efficiency: Factors influencing pulmonary function over time in children with asthma." Ann. Appl. Stat. 9 (2) 731 - 753, June 2015.


Received: 1 December 2013; Revised: 1 March 2015; Published: June 2015
First available in Project Euclid: 20 July 2015

zbMATH: 06499928
MathSciNet: MR3371333
Digital Object Identifier: 10.1214/15-AOAS826

Keywords: Biased sampling , childhood asthma , conditional likelihood , epidemiological study design , forced vital capacity , linear mixed effect models , longitudinal data analysis , multiple imputation , outcome dependent sampling , time-dependent covariates

Rights: Copyright © 2015 Institute of Mathematical Statistics

Vol.9 • No. 2 • June 2015
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