Results 31 to 40 of about 2,986,639 (394)
Scientific Reports, 2021 The prevalence of smokers is a major driver of lung cancer incidence in a population, though the “exposure–lag” effects are ill-defined. Here we present a multi-country ecological modelling study using a 30-year smoking prevalence history to quantify the
Daniel Robert Smith +4 more
doaj +1 more source
Dynamic Keynesian Model of Economic Growth with Memory and Lag
Mathematics, 2019 A mathematical model of economic growth with fading memory and continuous distribution of delay time is suggested. This model can be considered as a generalization of the standard Keynesian macroeconomic model.
Vasily E. Tarasov +1 more
doaj +1 more source
BMC Public Health, 2021 Environmental factors such as temperature, rainfall, and vegetation cover play a critical role in malaria transmission. However, quantifying the relationships between environmental factors and measures of disease burden relevant for public health can be ...
Jaffer Okiring +13 more
semanticscholar +1 more source
Reflection on modern methods: visualizing the effects of collinearity in distributed lag models.
International Journal of Epidemiology, 2021 Collinearity can be a problem in regression models. When examining the effects of an exposure at different time points, constrained distributed lag models can alleviate some of the problems caused by collinearity. Still, some consequences of collinearity
X. Basagaña, J. Barrera-Gómez
semanticscholar +1 more source
Exposure-Lag-Response in Longitudinal Studies: Application of Distributed-Lag Nonlinear Models in an Occupational Cohort. [PDF]
, 2018 Prolonged exposures can have complex relationships with health outcomes, as timing, duration, and intensity of exposure are all potentially relevant.
Brown, Daniel M +6 more
core +1 more source
Reducing and meta-analysing estimates from distributed lag non-linear models. [PDF]
, 2013 BACKGROUND: The two-stage time series design represents a powerful analytical tool in environmental epidemiology. Recently, models for both stages have been extended with the development of distributed lag non-linear models (DLNMs), a methodology for ...
Armstrong, Ben, Gasparrini, Antonio
core +1 more source
Distributed Lag Models for Hydrological Data [PDF]
Biometrics, 2013 AbstractSummaryThe distributed lag model (DLM), used most prominently in air pollution studies, finds application wherever the effect of a covariate is delayed and distributed through time. We specify modified formulations of DLMs to provide computationally attractive, flexible varying‐coefficient models that are applicable in any setting in which ...
Rushworth, Alastair M. +3 more
openaire +4 more sources
A Nonlinear Autoregressive Distributed Lag (NARDL) Analysis of the FTSE and S&P500 Indexes
Risks, 2021 The paper features an examination of the link between the behaviour of the FTSE 100 and S&P500 Indexes in both an autoregressive distributed lag ARDL, plus a nonlinear autoregressive distributed lag NARDL framework.
D. Allen, M. McAleer
semanticscholar +1 more source
Analisis Likuiditas Bank Umum Syariah dengan Pendekatan Autoregressive Distributed Lag (ARDL)
Al-tijary, 2021 This study aims to determine the influence of internal and external factors on the liquidity of Islamic banks. The research observation period was from January 2015 to April 2019 using the autoregressive distributed lag (ARDL) data processing method ...
Bintang Putri Pertiwi, Heri Sudarsono
doaj +1 more source
Extensions of the distributed lag non-linear model (DLNM) to account for cumulative mortality
Environmental science and pollution research international, 2021 The effects of meteorological factors on health outcomes have gained popularity due to climate change, resulting in a general rise in temperature and abnormal climatic extremes.
Chao-Yu Guo +3 more
semanticscholar +1 more source