NCJ Number
311192
Journal
Statistical Papers Volume: 57 Dated: 2016 Pages: 929-938
Date Published
August 2016
Length
10 pages
Abstract
Inverse prediction (IP) is reputed to be computationally inconvenient for multivariate responses. This paper describes how IP can be formulated in terms of a general linear mixed model, along with a flexible modeling approach for both mean vectors and variance–covariance matrices. It illustrates that results can be had as standard output from widely-available statistical computing packages.
(Publisher abstract provided.)
Date Published: August 1, 2016