Multiple imputation of missing data in clinical longitudinal studies and its sensitivity analyses / 中国临床药理学与治疗学
Chinese Journal of Clinical Pharmacology and Therapeutics
;
(12): 1037-1041, 2021.
Artículo
en Chino
| WPRIM
| ID: wpr-1014974
ABSTRACT
AIM:
To guide the multiple imputation of missing data in clinical longitudinal studies and its sensitivity analyses, and highlight the importance of sensitivity analyses by taking the clinical trial of Qizhitongluo Capsule in treating ischemic stroke as an example.METHODS:
To implement PROC MI process in SAS to perform multiple imputation and its sensitivity analysis.RESULTS:
In the example, after multiple imputation, improvements in lower limb motor scores of the Qizhitongluo group were greater than those of the placebo group (all P<0.01), and the results of two sensitivity analyses under "missing not at random" were consistent with those under "missing at random".CONCLUSION:
Multiple imputations combined with sensitivity analyses can ensure a robust result. It is recommended that clinical researchers perform sensitivity analyses after filling missing data.
Texto completo:
Disponible
Índice:
WPRIM (Pacífico Occidental)
Idioma:
Chino
Revista:
Chinese Journal of Clinical Pharmacology and Therapeutics
Año:
2021
Tipo del documento:
Artículo
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