Cite Them Right 11th edition - Harvard

Ren, J., Bushmakin, A.G., Cislo, P.R., Abraham, L., Cappelleri, J.C., Dworkin, R.H. und Farrar, J.T. (2025) „Meaningful within-patient change for clinical outcome assessments: model-based approach versus cumulative distribution functions.“, Journal of Biopharmaceutical Statistics, 35(5), S. 826-838. doi:10.1080/10543406.2023.2281575.

Chicago Manual of Style 17th edition (full note)

Ren, Jinma, Andrew G. Bushmakin, Paul R. Cislo, Lucy Abraham, Joseph C. Cappelleri, Robert H. Dworkin, und John T. Farrar. „Meaningful Within-Patient Change for Clinical Outcome Assessments: Model-Based Approach Versus Cumulative Distribution Functions.“. Journal of Biopharmaceutical Statistics 35, Nr. 5 (1. August 2025): 826-38. https://doi.org/10.1080/10543406.2023.2281575.

American Psychological Association 7th edition

Ren, J., Bushmakin, A. G., Cislo, P. R., Abraham, L., Cappelleri, J. C., Dworkin, R. H., & Farrar, J. T. (2025). Meaningful within-patient change for clinical outcome assessments: model-based approach versus cumulative distribution functions. Journal of Biopharmaceutical Statistics, 35(5), 826-838. https://doi.org/10.1080/10543406.2023.2281575

Modern Language Association 9th edition

Ren, J., A. G. Bushmakin, P. R. Cislo, L. Abraham, J. C. Cappelleri, R. H. Dworkin, und J. T. Farrar. „Meaningful Within-Patient Change for Clinical Outcome Assessments: Model-Based Approach Versus Cumulative Distribution Functions.“. Journal of Biopharmaceutical Statistics, Bd. 35, Nr. 5, August 2025, S. 826-38, https://doi.org/10.1080/10543406.2023.2281575.

ISO-690 (author-date, Deutsch)

REN, Jinma, Andrew G. BUSHMAKIN, Paul R. CISLO, Lucy ABRAHAM, Joseph C. CAPPELLERI, Robert H. DWORKIN und John T. FARRAR, 2025. Meaningful within-patient change for clinical outcome assessments: model-based approach versus cumulative distribution functions. Journal of Biopharmaceutical Statistics. 1 August 2025. Bd. 35, Nr. 5, S. 826-838. DOI 10.1080/10543406.2023.2281575

Achtung: Diese Zitate sind unter Umständen nicht zu 100% korrekt.