Bias Amplification and Variance Inflation in Distributed Lag Models Using Low-Spatial-Resolution Data.

ABSTRACT: Distributed lag models (DLMs) are often used to estimate lagged associations and identify critical exposure windows. In a simulation study of prenatal nitrogen dioxide (NO2) exposure and birth weight, we demonstrate that bias amplification and variance inflation can manifest under certain combinations of DLM estimation approaches and time-trend adjustment methods when using low-spatial-resolution exposures with extended lags. Our simulations showed that when using high-spatial-resolution exposure data, any time-trend adjustment method produced low bias and nominal coverage for the distributed lag estimator. When using either low- or no-spatial-resolution exposures, bias due to time trends was amplified for all adjustment methods. Variance inflation was higher in low- or no-spatial-resoluti

SUBMITTER: Leung M 

PROVIDER: S-EPMC10404064 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature