Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download Abstract
Document related concepts
Forecasting wikipedia , lookup
Regression toward the mean wikipedia , lookup
Least squares wikipedia , lookup
German tank problem wikipedia , lookup
Linear regression wikipedia , lookup
Maximum likelihood estimation wikipedia , lookup
Resampling (statistics) wikipedia , lookup
Transcript
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”
