dental-statistical-forensics

Dental study audits check SD/IQR, confidence intervals, effect sizes, and missing data to verify conclusions. A 12-point audit framework evaluates continuous, binary, diagnostic, and time-to-event outcomes to ensure reported clinical thresholds match statistical evidence.

Unit-of-analysis errors in dental studies happen when nested data, multiple implants, or multiple sites are treated as independent observations. Clustering checks detect these structural issues to prevent effect size misinterpretation and ensure accurate evidence critique.

Yes, statistical audits apply to diagnostic and time-to-event outcomes in dental papers. The audit evaluates SD/IQR, confidence intervals, MCID, and missing data across these outcome types to produce structured, decision-ready outputs for researchers and clinicians.

Yes, the dental study audit supports systematic reviews and evidence tables. It provides deterministic helper scripts and structured outputs designed for downstream replication, enabling researchers to critique clinical thresholds and numerical results across multiple papers.

Auditing clinical thresholds and missing data is limited by the completeness of reported numerical values in the source paper. If a dental study omits SD/CI, effect sizes, or dispersion metrics, the 12-point audit cannot fully verify whether conclusions are supported by the data.