PT  - JOURNAL ARTICLE
AU  - Chu, Xiajing
AU  - Chu, Derek K
AU  - Ren, Junjie
AU  - Brignardello-Petersen, Romina
AU  - Yang, Kehu
AU  - Guyatt, Gordon H
AU  - Lehana, Thabane
TI  - Completeness of reporting of simulation studies on responder analysis methods and simulation performance: a methodological survey
AID  - 10.1136/bmjopen-2024-096107
DP  - 2025 May 01
TA  - BMJ Open
PG  - e096107
VI  - 15
IP  - 5
4099  - http://bmjopen.bmj.com/content/15/5/e096107.short
4100  - http://bmjopen.bmj.com/content/15/5/e096107.full
SO  - BMJ Open2025 May 01; 15
AB  - Objectives To evaluate the completeness of reporting of simulation studies on responder analysis methods and simulation performance.Design Systematic methodological survey.Data sources We searched Embase, MEDLINE (via Ovid), PubMed and Web of Science Core Collection from inception to 9 October 2023.Eligibility criteria We included simulation studies comparing responder analysis methods and assessing simulation performance (bias, accuracy, precision or variance, power, type I and II errors and coverage).Data extraction and synthesis Two independent reviewers extracted data and assessed simulation performance. We used descriptive analyses to summarise reporting quality and simulation performance.Results We identified seven simulation studies exploring augmented binary methods, distributional methods and model-based methods. No studies reported the starting seed, occurrence of failures during simulations, the random number generator used and the number of simulations. No studies reported simulation accuracy. Responder analysis results were not significantly influenced by covariate adjustment. Distributional methods remained adaptable even with skewed data. Compared with standard binary methods, augmented binary methods generated increased power and precision. When the threshold is in the tail of the distribution, a simple asymptotic Bayesian (SAB) distributional approach may not reduce uncertainty but can improve precision.Conclusion Simulation studies comparing responder analysis methods exhibit suboptimal reporting quality. Compared with standard binary methods, augmented binary methods, distributional methods and model-based methods may be better choices, but there is no best one.Data are available upon reasonable request.