Universal optimality of Patterson's crossover designs
Kirti R. Shah, Mausumi Bose, Damaraju Raghavarao
Abstract
We show that the balanced crossover designs given by Patterson [Biometrika 39 (1952) 32--48] are (a) universally optimal (UO) for the joint estimation of direct and residual effects when the competing class is the class of connected binary designs and (b) UO for the estimation of direct (residual) effects when the competing class of designs is the class of connected designs (which includes the connected binary designs) in which no treatment is given to the same subject in consecutive periods. In both results, the formulation of UO is as given by Shah and Sinha [Unpublished manuscript (2002)]. Further, we introduce a functional of practical interest, involving both direct and residual effects, and establish (c) optimality of Patterson's designs with respect to this functional when the class of competing designs is as in (b) above.
Create a lesson
Related papers
Conformal Prediction Through the Lens of Hypothesis Testing: Universality, Impossibility, and Optimality
Ryan J. Tibshirani, Rina Foygel Barber, Aaditya Ramdas
Connecting Riemannian Geometry and Statistical Inference for Correlation Matrices
Argyn Kuketayev
How far can symmetry help? Phase transitions and symmetry selection in sparse functional data analysis
Jocelyn Nembe
Posterior consistency for subdiffusion inverse problems
Haoyu Lu, Shaokang Zu, Junxiong Jia
Dimension comparison for Student's statistic under symmetric unimodality
Jacopo Lenzi
Statistical Properties of Nonparametric MLE under Laplace Noise
Yifei Xiong, Nianqiao Phyllis Ju, Vinayak Rao