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II JIPE
ANÁLISIS SEMIPARAMÉTRICO Y NO PARAMÉTRICO DE
OBSERVACIONES INTERVALO CENSURADAS TIPO I Y
SUJETAS A MALA CLASIFICACIÓN DE LA RESPUESTA
Giancarlo Sal y Rosas
Global Health & Biostatistics, University of Washington .
Resumen
In this article, we present nonparametric and semiparametric methods to analyze current status data
subject to outcome misclassification. Our methods use nonparametric maximum likelihood estimation
(NPMLE) to estimate the distribution function of the failure time when sensitivity and specificity are
known and may vary among subgroups. A nonparametric test is proposed for the two sample hypothesis testing. In regression analysis, we apply the Cox proportional hazard model and likelihood ratio
based confidence intervals for the regression coefficients are proposed. Our methods are motivated and
demonstrated by data collected from an infectious disease study in Seattle, WA.
“II Jornada Internacional de Probabilidad y de Estadı́stica”