Efficiency of nearest neighbour balanced block designs for correlated observations

Abstract

Block designs for observations correlated in one dimension are investigated. Nearest neighbour balanced block designs turn out to be optimal for autoregressive correlation models when generalized least squares estimation is used. Performance of these designs for other correlation models is shown to be quite satisfactory. The efficiency of the proposed designs in comparison to the randomized block designs is computed and tabulated for some cases.