ArticlePharmacoepidemiology and drug safety2015
On the role of marginal confounder prevalence - implications for the high-dimensional propensity score algorithm.
Article in Pharmacoepidemiology and drug safety, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Reported evidence on the effectiveness of mass media interventions in increasing knowledge and use of family planning in low and middle-income countries: a systematic mixed methods review.Journal of global health · 2019Pooled it
- Applying High-Dimensional Propensity Scores in a Study of Inhaled Corticosteroids and COVID-19 Outcomes.Pharmacoepidemiology and drug safety · 2025Article
- Glucagon-like Peptide-1 Receptor Agonists in Asthma Exacerbations: An Application of High-Dimensional Iterative Causal Forest to Identify Subgroups.Pharmacoepidemiology and drug safety · 2025Article
- Application of High-Dimensional Propensity Score Methods to the National Health and Aging Trends Study.The journals of gerontology. Series A, Biological sciences and medical sciences · 2024Article
- High-dimensional propensity scores for empirical covariate selection in secondary database studies: Planning, implementation, and reporting.Pharmacoepidemiology and drug safety · 2023Article
- Transparency of high-dimensional propensity score analyses: Guidance for diagnostics and reporting.Pharmacoepidemiology and drug safety · 2022Article
- A comparison of confounder selection and adjustment methods for estimating causal effects using large healthcare databases.Pharmacoepidemiology and drug safety · 2022Article
- Building a framework for the evaluation of knowledge translation for the Canadian Network for Observational Drug Effect Studies.Pharmacoepidemiology and drug safety · 2020Article
- Automated data-adaptive analytics for electronic healthcare data to study causal treatment effects.Clinical epidemiology · 2018Review
- Propensity Scores in Pharmacoepidemiology: Beyond the Horizon.Current epidemiology reports · 2017Article
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Authors and funding
3 authors.
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Abstract
purposeThe high-dimensional propensity score algorithm attempts to improve control of confounding in typical treatment effect studies in pharmacoepidemiology and is increasingly being used for the analysis of large administrative databases. Within this multi-step variable selection algorithm, the marginal prevalence of non-zero covariate values is considered to be an indicator for a count variable's potential confounding impact. We investigate the role of the marginal prevalence of confounder variables on potentially caused bias magnitudes when estimating risk ratios in point exposure studies with binary outcomes.
methodsWe apply the law of total probability in conjunction with an established bias formula to derive and illustrate relative bias boundaries with respect to marginal confounder prevalence.
resultsWe show that maximum possible bias magnitudes can occur at any marginal prevalence level of a binary confounder variable. In particular, we demonstrate that, in case of rare or very common exposures, low and high prevalent confounder variables can still have large confounding impact on estimated risk ratios.
conclusionsCovariate pre-selection by prevalence may lead to sub-optimal confounder sampling within the high-dimensional propensity score algorithm. While we believe that the high-dimensional propensity score has important benefits in large-scale pharmacoepidemiologic studies, we recommend omitting the prevalence-based empirical identification of candidate covariates.
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