Yue Yu : Assessment of Agreement in Linear/Generalized Linear Mixed Models

Posted by Jie Yang , part of the Statistics and Data Science Seminar.

At

Feb. 8, 2012, 4 p.m.

In

SEO 636

Abstract

Study of measuring agreement is mainly aimed to answer one question, whether the readings from one instrument/method agree with the ones from another instrument/method. In this talk, we are going to present a general method to assess agreement for a wide range of data types with repeated measurements using linear and generalized linear mixed models. Likelihood-based approaches are developed to estimate all the within- and between-instrument agreement statistics. and asymptotic properties of these agreement estimates are discussed for different data structures. Furthermore, our method has the merit of handling missing values and covariates naturally. And a new set of restricted agreement statistics is proposed in order to capture the true random variations and between-instrument effects rather than the covariate effects. Simulations and several case studies, involving method comparison and bioequivalence, are used to show the accuracy and effectiveness of our method.