In this article, we consider the statistical analysis of a current status data design when the laboratory test that measures the outcome of interest is subject to error and when some visits are informative due to symptomatic events. Our proposed methodology establishes a general framework using the EM algorithm to estimate the cumulative distribution function of the disease of interest (one sample problem). In addition, we proposed a statistic based on the mean difference of the survival functions of two groups for the two-sample hypothesis testing problem. Finally, we extend the EM algorithm to implement a proportional hazard model that takes into account the misclassification rates and the symptomatic data. Our methods are motivated and demonstrated by data collected from an infectious disease study in Seattle, WA.

2014 Joint Statistical Meetings
2 al 7 de agosto de 2014
Boston, Massachusetts, USA

 

 

 

Participante(s):
SAL Y ROSAS, Giancarlo

Institución responsable:
PUCP
Año: 2014
Ponencia presentada en Nombre del evento: Joint Statistical Meeting
Ciudad: Boston, Massachusetts, USA
Url: http://www.amstat.org/meetings/jsm/2014/onlineprogram/AbstractDetails.cfm?abstractid=313616