Optimal Designs for Carry Over Effects the Case of Two Treatment and Four Periods

The optimal cross-over experimental designs are derived in experiments with two treatments, four periods, and an experimental unit. The results are given for the values n = 0mod4, 1mod4, 2mod4 and 3mod4. The criterion being the minimization of the variance of the estimated carry over effect.

Optimal Repeated Measurements for Two Treatment Designs with Dependent Observations: The Case of Compound Symmetry

In this paper, we construct optimal repeated measurement designs of two treatments for estimating direct effects, and we examine the case of compound symmetry dependency. We present the model and the design that minimizes the variance of the estimated difference of the two treatments. The optimal designs with dependent observations in a compound symmetry model are the same as in the case of independent observations.

Regulatory affairs in biotechnology: optimal statistical designs for biomedical experiments

One of the major issues in all applications of biotechnology is how to regulate the process through which new technological information is produced. The end products of biotechnological applications are diverse (e.g., better drugs, better interventions, better fertilizers). Such applications should be properly regulated to obtain valid scientific findings in the most efficient way possible. Some statistically optimal designs are more popularly employed than others as regulatory tools in medical, pharmaceutical and clinical trials. The statistical and practical properties (strengths and weaknesses) are presented to better appreciate their optimality. Recent developments on some related issues are also reviewed.

Analysis of a within-subject design with covariates

This paper deals with a method of analyzing incomplete data, forming a monotone pattern, from a within-subject design with baseline measurements. An assumption of multivariate normality with antedependence structure is made for both the baseline measurements and the response measurements. Adjusted means for the period-by-sequence cells and their dispersion matrix are obtained. Large sample tests are proposed for testing various hypotheses. A numerical example is given to illustrate the methodology.

Multi-period crossover trials

This paper presents a review of crossover designs for use in medical applications which have three or more treatment periods. Only outcomes which can be analysed as continuous variables are considered. Designs which purport to allow for carryover effects are reviewed in detail, as are methods for analysing data collected in such trials. In practice, it is often possible to eliminate carryover by interposing sufficiently long 'washout' periods between successive treatments, and suitable designs for this case are also mentioned. Much current practice revolves around a model which has been widely criticized: the shortcomings of this model and the implications of possible remedies, for design as well as analysis, are discussed.