Non-parametric estimates of overlap.
Stat Med
; 20(2): 215-36, 2001 Jan 30.
Article
en En
| MEDLINE
| ID: mdl-11169598
Kernel densities provide accurate non-parametric estimates of the overlapping coefficient or the proportion of similar responses (PSR) in two populations. Non-parametric estimates avoid strong assumptions on the shape of the populations, such as normality or equal variance, and possess sampling variation approaching that of parametric estimates. We obtain accurate standard error estimates by bootstrap resampling. We illustrate the practical use of these methods in two examples and use simulations to explore the properties of the estimators under various sampling situations.
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Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Simulación por Computador
/
Interpretación Estadística de Datos
/
Estadísticas no Paramétricas
Límite:
Female
/
Humans
Idioma:
En
Revista:
Stat Med
Año:
2001
Tipo del documento:
Article
País de afiliación:
Estados Unidos
Pais de publicación:
Reino Unido