Exploring the impact of selection bias in observational studies of COVID-19: a simulation study.

ABSTRACT:

Background

Non-random selection of analytic subsamples could introduce selection bias in observational studies. We explored the potential presence and impact of selection in studies of SARS-CoV-2 infection and COVID-19 prognosis.

Methods

We tested the association of a broad range of characteristics with selection into COVID-19 analytic subsamples in the Avon Longitudinal Study of Parents and Children (ALSPAC) and UK Biobank (UKB). We then conducted empirical analyses and simulations to explore the potential presence, direction and magnitude of bias due to this selection (relative to our defined UK-based adult target populations) when estimating the association of body mass index (BMI) with SARS-CoV-2 infection and death-with-COVID-19.

Results

In both cohorts, a broad

SUBMITTER: Millard LAC 

PROVIDER: S-EPMC9908043 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature