Abstract
Summary: The method of adjusting plot values by covariance on neighbouring plots in randomized field experiments, suggested by Papadakis in 1937, is re-examined theoretically for both one-dimensional and two-dimensional layouts, making use of Markovian and autonormal models. The gain in efficiency over orthodox randomized block analysis can be appreciable when the number of treatments is fairly large, and can be increased by iterating the analysis; this also reduces the discrepancy between the apparent accuracy from the residual sum of squares, and the true accuracy of the treatment comparisons after adjustment. Some illustrative examples are included.