Estimands and estimators of two-level methods using return to baseline strategy for longitudinal clinical trials with incomplete daily patient reported outcomes.
J Biopharm Stat
; 33(4): 425-438, 2023 Jul 04.
Article
em En
| MEDLINE
| ID: mdl-34162312
ABSTRACT
Returning to baseline (RTB) has been a practical method for handling missing data. Here we consider longitudinal clinical trials with daily patient reported outcomes (PROs), where efficacy endpoints are often defined as the average daily values in a cycle (such as a month or a week). The conventional method treats data at cycle level and ignores daily values. In this paper, we build a two-level constrained longitudinal data analysis (cLDA) model on daily values and propose two-level RTB method to impute daily values. Standard multiple imputation (MI) approach and likelihood-based approach are proposed and evaluated by simulations.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Projetos de Pesquisa
Aspecto:
Patient_preference
Limite:
Humans
Idioma:
En
Revista:
J Biopharm Stat
Ano de publicação:
2023
Tipo de documento:
Article