Treed distributed lag nonlinear models. [PDF]
Biostatistics, 2022 In studies of maternal exposure to air pollution, a children's health outcome is regressed on exposures observed during pregnancy. The distributed lag nonlinear model (DLNM) is a statistical method commonly implemented to estimate an exposure-time ...
Mork D, Wilson A.
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Distributed lag non-linear models [PDF]
Statistics in Medicine, 2010 Environmental stressors often show effects that are delayed in time, requiring the use of statistical models that are flexible enough to describe the additional time dimension of the exposure–response relationship.
A. Gasparrini, B. Armstrong, M. Kenward
semanticscholar +4 more sources
Indonesian Export Analysis: Autoregressive Distributed Lag (ARDL) Model Approach [PDF]
Journal of Economics, Business & Accountancy Ventura, 2021 There are some factors predicted tohave an effect on the countries’ economic devlopment. This study aimed to analyze the long-term and short-term effects of In-flation, Exchange Rate, and Foreign Economic Growth (the destination of the United States ...
Syarifah Labibah +2 more
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Multiple exposure distributed lag models with variable selection. [PDF]
Biostatistics, 2023 Distributed lag models are useful in environmental epidemiology as they allow the user to investigate critical windows of exposure, defined as the time periods during which exposure to a pollutant adversely affects health outcomes.
Antonelli J, Wilson A, Coull BA.
europepmc +3 more sources
Spatial Bayesian distributed lag non-linear models (SB-DLNM) for small-area exposure-lag-response epidemiological modelling. [PDF]
Int J EpidemiolBackground Distributed lag non-linear models (DLNMs) are the reference framework for modelling lagged non-linear associations. They are usually used in large-scale multi-location studies. Attempts to study these associations in small areas either did not
Quijal-Zamorano M +3 more
europepmc +2 more sources
dLagM: An R package for distributed lag models and ARDL bounds testing.
PLoS ONE, 2020 In this article, we introduce the R package dLagM for the implementation of distributed lag models and autoregressive distributed lag (ARDL) bounds testing to explore the short and long-run relationships between dependent and independent time series ...
Haydar Demirhan
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Autoregressive distributed lag models and cointegration [PDF]
Allgemeines Statistisches Archiv, 2006 This paper considers cointegration analysis within an autoregressive distributed lag (ADL) framework. First, different reparameterizations and interpretations are reviewed.
Hassler, Uwe, Wolters, Jürgen
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Modeling exposure-lag-response associations with distributed lag non-linear models. [PDF]
Statistics in Medicine, 2013 In biomedical research, a health effect is frequently associated with protracted exposures of varying intensity sustained in the past. The main complexity of modeling and interpreting such phenomena lies in the additional temporal dimension needed to ...
Gasparrini, Antonio
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Attributable risk from distributed lag models. [PDF]
BMC Medical Research Methodology, 2014 BACKGROUND: Measures of attributable risk are an integral part of epidemiological analyses, particularly when aimed at the planning and evaluation of public health interventions.
Gasparrini, Antonio, Leone, Michela
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A novel spatial heteroscedastic generalized additive distributed lag model for the spatiotemporal relation between PM2.5and cardiovascular hospitalization [PDF]
Scientific ReportsMany studies have examined the impact of air pollution on cardiovascular hospitalization (CVH), but few have looked at the delayed effects of air pollution on CVH.
Ali Hadianfar +3 more
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