ArticleJournal of the Royal Statistical Society. Series C, Applied statistics2019
Distributed Lag Interaction Models with Two Pollutants.
Article in Journal of the Royal Statistical Society. Series C, Applied statistics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Article
- Smooth and shape-constrained quantile distributed lag models.Biometrics · 2025Article
- Dynamic Single-Index Scalar-On-Function Model.Statistics in medicine · 2025Article
- LOW-RANK LONGITUDINAL FACTOR REGRESSION WITH APPLICATION TO CHEMICAL MIXTURES.The annals of applied statistics · 2025Article
- The impact of air pollutants on emergency ambulance dispatches due to mental and behavioral disorders in Shenzhen, China.BMC public health · 2025Article
- Multiple exposure distributed lag models with variable selection.Biostatistics (Oxford, England) · 2023Article
- Semiparametric distributed lag quantile regression for modeling time-dependent exposure mixtures.Biometrics · 2023Article
- Estimating perinatal critical windows of susceptibility to environmental mixtures via structured Bayesian regression tree pairs.Biometrics · 2023Article
- Adverse effects of temperature on perinatal and pregnancy outcomes: methodological challenges and knowledge gaps.Frontiers in public health · 2023Review
- CRITICAL WINDOW VARIABLE SELECTION FOR MIXTURES: ESTIMATING THE IMPACT OF MULTIPLE AIR POLLUTANTS ON STILLBIRTH.The annals of applied statistics · 2022Article
- KERNEL MACHINE AND DISTRIBUTED LAG MODELS FOR ASSESSING WINDOWS OF SUSCEPTIBILITY TO ENVIRONMENTAL MIXTURES IN CHILDREN'S HEALTH STUDIES.The annals of applied statistics · 2022Article
- A spatially varying distributed lag model with application to an air pollution and term low birth weight study.Journal of the Royal Statistical Society. Series C, Applied statistics · 2020Article
- Temperature as a modifier of the effects of air pollution on cardiovascular disease hospital admissions in Cape Town, South Africa.Environmental science and pollution research international · 2020Article
- Selection of nonlinear interactions by a forward stepwise algorithm: Application to identifying environmental chemical mixtures affecting health outcomes.Statistics in medicine · 2019Article
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3 authors.
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Abstract
Distributed lag models (DLMs) have been widely used in environmental epidemiology to quantify the lagged effects of air pollution on a health outcome of interest such as mortality and morbidity. Most previous DLM approaches only consider one pollutant at a time. In this article, we propose distributed lag interaction model (DLIM) to characterize the joint lagged effect of two pollutants. One natural way to model the interaction surface is by assuming that the underlying basis functions are tensor products of the basis functions that generate the main-effect distributed lag functions. We extend Tukey's one-degree-of-freedom interaction structure to the two-dimensional DLM context. We also consider shrinkage versions of the two to allow departure from the specified Tukey's interaction structure and achieve bias-variance tradeoff. We derive the marginal lag effects of one pollutant when the other pollutant is fixed at certain quantiles. In a simulation study, we show that the shrinkage methods have better average performance in terms of mean squared error (MSE) across different scenarios. We illustrate the proposed methods by using the National Morbidity, Mortality, and Air Pollution Study (NMMAPS) data to model the joint effects of PM
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