JSM 2005 Online Program

Abstract #303852

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	66
Type:	Contributed
Date/Time:	Sunday, August 7, 2005 : 4:00 PM to 5:50 PM
Sponsor:	ENAR
Abstract - #303852
Title:	Likelihood-based Approach for Left-censored Covariates
Author(s):	Gina D'Angelo*+ and Lisa Weissfeld
Companies:	University of Pittsburgh and University of Pittsburgh
Address:	144 N Dithridge St Apt 203, Pittsburgh, PA, 15213, United States
Keywords:	left censored covariate ; semiparametric ; likelihood-based
Abstract:	Truncated and censored data methodology has been developed throughout the last 30 years with the focus on the outcome variable. This has led to the development of models such as the Tobit regression model for censored outcome data in addition to numerous models for truncated data. Another commonly encountered problem is that of censored covariate data. This type of data generally is observed in the laboratory setting, where the lower limit of detection of an assay often is observed. To address this problem, we propose two methods to estimate the coefficients and their standard errors for a regression model with a left-censored covariate using likelihood-based techniques and estimating equation techniques. These methods will be compared to a standard method of filling in the censored value with the lower threshold value. The application of these methods is illustrated in a sepsis study conducted at the University of Pittsburgh. One aim is to determine the relationship between sepsis status and measures of inflammation, such as interleukin-6 and interleukin-10.

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