Statistics and Data Science Seminar
Yue Yu
University of Illinois at Chicago
Assessment of Agreement in Linear/Generalized Linear Mixed Models
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.
Wednesday February 8, 2012 at 4:00 PM in SEO 636