Litcius/Paper detail

Quantitative Assessment of Systematic Bias: A Guide for Researchers

Julia C. Bond, Matthew P. Fox, Lauren A. Wise, Brenda Heaton

2023Journal of Dental Research15 citationsDOIOpen Access PDF

Abstract

Observational research provides valuable opportunities to advance oral health science but is limited by vulnerabilities to systematic bias, including unmeasured confounding, errors in variable measurement, or bias in the creation of study populations and/or analytic samples. The potential influence of systematic biases on observed results is often only briefly mentioned among the discussion of limitations of a given study, despite existing methods that support detailed assessments of their potential effects. Quantitative bias analysis is a set of methodological techniques that, when applied to observational data, can provide important context to aid in the interpretation and integration of observational research findings into the broader body of oral health research. Specifically, these methods were developed to provide quantitative estimates of the potential magnitude and direction of the influence of systematic biases on observed results. We aim to encourage and facilitate the broad adoption of quantitative bias analyses into observational oral health research. To this end, we provide an overview of quantitative bias analysis techniques, including a step-by-step implementation guide. We also provide a detailed appendix that guides readers through an applied example using real data obtained from a prospective observational cohort study of preconception periodontitis in relation to time to pregnancy. Quantitative bias analysis methods are available to all investigators. When appropriately applied to observational studies, findings from such studies can have a greater impact in the broader research context.

Topics & Concepts

Observational studyContext (archaeology)Observational methods in psychologyConfoundingSystematic reviewMeta-analysisPublication biasClinical study designData scienceComputer scienceMEDLINEStatisticsMedicineClinical trialMathematicsGeographyLawPolitical sciencePathologyInternal medicineArchaeologyStatistical Methods in EpidemiologyReliability and Agreement in MeasurementAdvanced Causal Inference Techniques
Quantitative Assessment of Systematic Bias: A Guide for Researchers | Litcius