Optimal design in multiple group random coefficient regression models

M. Prus

Random coefficient regression (RCR) models are popular in many field of statistical application, for example in biosciences or engineering sciences. In these models observational units (individuals) are assumed to come from the same population with an unknown population mean and differ from each other by individual parameters. In multiple group RCR models individuals in different groups get different kinds of treatment. In multiple group models with fixed group sizes, where the unknown mean parameters may differ from group to group, statistical analysis can be performed in each group separately. In contrast to that this talk presents analytical results for optimal designs in models, where there is a common population mean for all individuals across all groups and where group sizes have to be also optimized.

Palabras clave: Random coefficient

M05.1 Sesión Hispano-Alemana: Diseño Óptimo de Experimentos
6 de septiembre de 2016  11:00
0.02 - Aula de proyectos 1

G. Sánchez León, J. López Fidalgo

K. Schorning

C. Neumann