Past developments and future opportunities in the design and analysis of crop experiments

A review of papers on the statistical design and analysis of experiments published in the Journal of Agricultural Science, Cambridge, over the last 100 years is presented. The development of significant ideas in the practical design of field experiments is reviewed. Some possible future developments in the design of spatial field trials and computer-aided design of experiments are discussed

(Dt,C) Optimal run orders.

Cost considerations have rarely been taken into account in optimum design theory. A few authors consider measurement costs, i.e. the costs associated with a particular factor level combination. A second cost approach results from the fact that it is often expensive to change factor levels from one observation to another. We refer to these costs as transition costs. In view of cost minimization, one should minimize the number of factor level changes. However, there is a substantial likelihood that there is some time order dependence in the results. Consequently, when considering both time order dependence and transition costs, an optimal ordering is not easy to find. There is precious little in the literature on how to select good time order sequences for arbitrary design problems and up to now, no thorough analysis of both costs is found in the literature. For arbitrary design problems, our proposed design algorithm incorporates cost considerations in optimum design construction and enables one to compute cost-efficient run orders that are optimally balanced for time trends. The results show that cost considerations in the construction of trend-resistant run orders entail considerable reductions in the total cost of an experiment and imply a large increase in the amount of information per unit cost.Optimal; Run orders;

A Generalized Procedure for Constructing Fractional Replicates

39 pages, 1 article*A Generalized Procedure for Constructing Fractional Replicates* (Paik, U. B.; Federer, W. T.) 39 page

Blocking Mixed-Level Factorials with SAS

Orthogonal array screening designs for mixed-level or asymmetric factorials have recently become popular. Tables of designs and software for creating these designs are readily available to practitioners. However, confounded block designs for mixed-level factorials are not as popular partly due to the fact that software for creating these designs has not been well publicized. Classical methods for creating confounded-block mixed-level factorials normally described in textbooks utilize modular arithmetic or finite fields. In the recent literature optimal design theory has also been proposed as method for creating these designs. Although no examples are shown in the online documentation, both classical and optimal confounded-block mixed-level factorials can be easily created using SAS data step programming in conjunction with proc plan, proc factex or proc optex. In this article we show examples of creating these designs in SAS, and we compare the properties of designs created by classical methods and optimal design theory

Optimal design procedures for two-level fractional factorial experiments given partial prior information about parameters

Design optimization for fractional factorial experiments by finite decision problem based on prior informatio

Treatment Design Definitions, Types, and Properties

21 pages, 1 article*Treatment Design Definitions, Types, and Properties* (Federer, W. T.) 21 page

On the Construction of Fractional Replicates with Special Reference to Saturated Designs

33 pages, 1 article*On the Construction of Fractional Replicates with Special Reference to Saturated Designs* (Paik, U. B.; Federer, W. T.) 33 page