J Biopharm Stat. 2026 May 24:1-17. doi: 10.1080/10543406.2026.2676019. Online ahead of print.
ABSTRACT
In clinical studies involving paired organs (e.g. eyes or ears), correlated binary outcomes necessitate specialized statistical methods to account for intra-subject dependencies. This paper proposes a saddlepoint approximation (SA) method for constructing confidence intervals (CI) for risk differences in paired binary data under Donner’s correlation model. Compared to conventional approaches – Wald, likelihood ratio, score, and MOVER methods – the SA method explicitly incorporates higher-order moment information, offering improved accuracy in small-sample or rare-event settings. Simulation studies evaluate empirical coverage probability (ECP) and mean interval width (MIW) across varying correlation levels. Results demonstrate that SA consistently maintains ECPs near the nominal 95% level while achieving narrower intervals than competing methods, particularly under high correlation. In contrast, likelihood and score tests exhibit undercoverage, and Wald/MOVER intervals are overly conservative. An application to otitis media trial data further validates SA’s utility, yielding interpretable inferences for correlated bilateral outcomes. The proposed method bridges a critical gap in small-sample inference for risk differences, ensuring robustness without reliance on large-sample approximations.
PMID:42177767 | DOI:10.1080/10543406.2026.2676019
