JSM 2005 Online Program

Abstract #304500

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:	65
Type:	Contributed
Date/Time:	Sunday, August 7, 2005 : 4:00 PM to 5:50 PM
Sponsor:	General Methodology
Abstract - #304500
Title:	Higher-order Asymptotics for the Mixed Effects Linear Model
Author(s):	Sigfrido Iglesias-Gonzalez*+
Companies:	University of Toronto
Address:	Dept Of Statistics, Toronto, ON, MS5 3G3, Canada
Keywords:	higher order asymptotics ; higher order approximations ; mixed effects model ; confidence intervals ; barndorff-nielsen r* ; mixed linear model
Abstract:	Higher-order asymptotics for the construction of confidence intervals in the Gaussian Mixed Linear Model is discussed. The asymptotic framework in which the discussion is centered is provided by Bandorff-Nielsen's r* formula for a scalar parameter of interest. It is shown that the relevant quantities, some well known statistics, that define r* in this setting are obtainable already. In order to assess the performance of the r*-based confidence intervals, a simulation study is conducted in particular settings of interest in applications. The simulation extends to explore the effect of distribution misspecification. Particularly, the simulation is concerned with the effect of samples generated by heavy-tailed symmetric distributions. For comparison purposes, numeric work for standard first-order confidence intervals is presented.

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