Core concepts in statistics and research methods. Part 2: clinical research principles and observational studies

2025/01/15 by David W. Hewson, B. Stuart · 1 voice
Economics, Econometrics and Finance · Mathematics · #Advanced Causal Inference Techniques #Health Systems, Economic Evaluations, Quality of Life #Healthcare Policy and Management

paper · doi:10.1016/j.bjae.2024.11.006

openalex publication_date 2025/01/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/18

Abstract

• Primary clinical research can be categorised as either observational or experimental.• Bias is present in all observational studies.•The relationship between an exposure and outcome can be distorted by a third extraneous variable, a confounder.•Statistical strategies to address confounding include matching, stratification, regression, propensity scoring and instrumental variable analysis.•The main weakness of propensity scoring is that it can only control for known and measured confounding.

Citations

• An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies
• Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations
• The Environment and Disease: Association or Causation?
• Why Propensity Scores Should Not Be Used for Matching

Discussions

• 📘 New in #BJAEd: Revisit the fundamentals of clinical research with this clear guide to observational study design, bias, confounding & statistical methods. Essential reading for anaesthetists & res [bsky, 1 points, 0 comments]

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