Title	Robust designs for generalized linear mixed models
Creator	Sinha, Sanjoy
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2016-09-03T10:58
Description	Generalized linear mixed models (GLMMs) are commonly used for analyzing clustered correlated discrete binary and count data including longitudinal data and repeated measurements. We explore techniques for the design of experiments, where the design issue is formulated as a decision of choosing the values of the predictor(s) for GLMMs. We investigate sequential design methodologies when the fitted model is possibly of an incorrect parametric form. We assess the performance of the proposed design using a small simulation study.
Extent	31 minutes
Subject	Mathematics; Statistics
Type	Moving Image
File Format	video/mp4
Language	eng
Notes	Author affiliation: Carleton University
Series	BIRS Workshop Lecture Videos (Banff, Alta)
Date Available	2017-10-13
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivatives 4.0 International
DOI	10.14288/1.0357037
URI	http://hdl.handle.net/2429/63275
Affiliation	Non UBC
Peer Review Status	Unreviewed
Scholarly Level	Faculty
Rights URI	http://creativecommons.org/licenses/by-nc-nd/4.0/
Aggregated Source Repository	DSpace

Open Collections

BIRS Workshop Lecture Videos