Simulation-based sample-sizing and power calculations in logistic regression with partial prior information.
Pharm Stat
; 15(6): 507-516, 2016 11.
Article
en En
| MEDLINE
| ID: mdl-27588379
ABSTRACT
There have been many approximations developed for sample sizing of a logistic regression model with a single normally-distributed stimulus. Despite this, it has been recognised that there is no consensus as to the best method. In pharmaceutical drug development, simulation provides a powerful tool to characterise the operating characteristics of complex adaptive designs and is an ideal method for determining the sample size for such a problem. In this paper, we address some issues associated with applying simulation to determine the sample size for a given power in the context of logistic regression. These include efficient methods for evaluating the convolution of a logistic function and a normal density and an efficient heuristic approach to searching for the appropriate sample size. We illustrate our approach with three case studies. Copyright © 2016 John Wiley & Sons, Ltd.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Proyectos de Investigación
/
Diseño de Fármacos
/
Modelos Estadísticos
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
Pharm Stat
Asunto de la revista:
FARMACOLOGIA
Año:
2016
Tipo del documento:
Article
País de afiliación:
Reino Unido