Smiling through the gaps: Missing data solutions for periodontal estimates from partial-mouth exams

Music City Center 

Partial-mouth periodontal examinations (PMPE) are a suggested alternative to full mouth examinations in oral-health epidemiological studies. While more cost-effective and less burdensome for study participants, they often introduce systematic missingness leading to substantial underestimation of disease prevalence. Viewing the problem from an incomplete-data perspective, our previous work employed multiple imputation (MI) as a framework for representing observed patterns of association while also reflecting uncertainty in individual values. While the MI approach was helpful in reducing bias, questions remain as to the effectiveness of alternative modeling assumptions and missing-data approaches over our initial MI approach for estimating periodontal disease prevalence from PMPE designs. We will outline an evaluation of trade-offs between bias reduction, coverage, and robustness across each of the newly considered missing-data mechanisms using both empirical data and simulations. Our results will provide methodological insights for improving PMPE-based missing data in epidemiological studies.

Dentistry

Oral health

Missing data

Epidemiology

Periodontitis

Public health 

Biometrics Section