Construction of Partially Balanced Incomplete Block Designs with Nested Rows and Columns

A number of methods of construction of partially balanced incomplete block designs with nested rows and columns are developed and new balanced incomplete block designs with nested rows and columns are obtained as a by-product.     

Conditional Maximum Likelihood Estimation Following a Group Sequential Test

We consider estimation after a group sequential test. An estimator that is unbiased or has small bias may have substantial conditional bias (Troendle and Yu, 1999, Coburger and Wassmer, 2001). In this paper we derive the conditional maximum likelihood estimators of both the primary parameter and a secondary parameter, and investigate their properties within a conditional inference framework. The method applies to both the usual and adaptive group sequential test designs. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Magnetite biomineralization and geomagnetic sensitivity in higher animals: an update and recommendations for future study

Magnetite, the only known biogenic material with ferromagnetic properties, has been identified as a biochemical precipitate in three of the five kingdoms of living organisms, with a fossil record that now extends back nearly 2 billion years. In the magnetotactic bacteria, protoctists, and fish, single-domain crystals of magnetite are arranged in membrane-bound linear structures called magnetosomes, which function as biological bar magnets. Magnetosomes in all three of these groups bear an overall structural similarity to each other, which includes alignment of the individual crystallographic [111] directions parallel to the long axis. Although the magnetosomes represent only a small volume fraction in higher organisms, enough of these highly energetic structures are present to provide sensitivity to extremely small fluctuations and gradients in the background geomagnetic field. Previous experiments with elasmobranch fish are reexamined to test the hypothesis that gradients played a role in their successful geomagnetic conditioning, and a variety of four-turn coil designs are considered that could be used to test the various hypotheses proposed for them.     

A design criterion for symmetric model discrimination based on flexible nominal sets

Experimental design applications for discriminating between models have been hampered by the assumption to know beforehand which model is the true one, which is counter to the very aim of the experiment. Previous approaches to alleviate this requirement were either symmetrizations of asymmetric techniques, or Bayesian, minimax, and sequential approaches. Here we present a genuinely symmetric criterion based on a linearized distance between mean-value surfaces and the newly introduced tool of flexible nominal sets. We demonstrate the computational efficiency of the approach using the proposed criterion and provide a Monte-Carlo evaluation of its discrimination performance on the basis of the likelihood ratio. An application for a pair of competing models in enzyme kinetics is given.     

Binary Responses and the Three-period Cross-over

Problems with carry-over effects in the simple two-period cross-over have lead to interest in more complex cross-over designs. A method for analysing the optimum two-treatment three-period design with binary response variables is given by making a simple extension to Gart's logistic model. The method gives independent tests for, and estimates of the difference in treatment and first-order carry-over effects. An example of the analysis is given, using the loglinear models facility in GLIM.     

Likelihood-based experimental design for estimation of ED50

In selecting the best dosage choice for the estimation of ED50, it is natural to try to minimize the length of the confidence intervals. In this presentation, the dose allocation that minimizes the length of the likelihood-based confidence intervals is presented and compared with alternative allocations that have been proposed based on the length of different types of confidence intervals, such as those based on the asymptotic variance or on Fieller's Theorem. Effective strategies to deal with the parameter dependence of these allocations are explored. A series of experiments to evaluate the effect of small doses per fraction on the radiation tolerance of the rat cervical spinal cord provide the motivation and an illustration for the proposed procedures.     

High-throughput optimization by statistical designs: example with rat liver slices cryopreservation

The purpose of this study was to optimize cryopreservation conditions of rat liver slices in a high-throughput format, with focus on reproducibility. A statistical design of 32 experiments was performed and intracellular lactate dehydrogenase (LDHi) activity and antipyrine (AP) metabolism were evaluated as biomarkers. At freezing, modified University of Wisconsin solution was better than Williams'E medium, and pure dimethyl sulfoxide was better than a cryoprotectant mixture. The best cryoprotectant concentrations were 10% for LDHi and 20% for AP metabolism. Fetal calf serum could be used at 50 or 80%, and incubation of slices with the cryoprotectant could last 10 or 20 min. At thawing, 42 degrees C was better than 22 degrees C. After thawing, 1h was better than 3h of preculture. Cryopreservation increased the interslice variability of the biomarkers. After cryopreservation, LDHi and AP metabolism levels were up to 84 and 80% of fresh values. However, these high levels were not reproducibly achieved. Two factors involved in the day-to-day variability of LDHi were identified: the incubation time with the cryoprotectant and the preculture time. In conclusion, the statistical design was very efficient to quickly determine optimized conditions by simultaneously measuring the role of numerous factors. The cryopreservation procedure developed appears suitable for qualitative metabolic profiling studies.     

Conditional logistic analysis of case-control studies with complex sampling

Methods for the analysis of unmatched case-control data based on a finite population sampling model are developed. Under this model, and the prospective logistic model for disease probabilities, a likelihood for case-control data that accommodates very general sampling of controls is derived. This likelihood has the form of a weighted conditional logistic likelihood. The flexibility of the methods is illustrated by providing a number of control sampling designs and a general scheme for their analyses. These include frequency matching, counter-matching, case-base, randomized recruitment, and quota sampling. A study of risk factors for childhood asthma illustrates an application of the counter-matching design. Some asymptotic efficiency results are presented and computational methods discussed. Further, it is shown that a 'marginal' likelihood provides a link to unconditional logistic methods. The methods are examined in a simulation study that compares frequency and counter-matching using conditional and unconditional logistic analyses and indicate that the conditional logistic likelihood has superior efficiency. Extensions that accommodate sampling of cases and multistage designs are presented. Finally, we compare the analysis methods presented here to other approaches, compare counter-matching and two-stage designs, and suggest areas for further research.To whom correspondence should be addressed.     

Minimax D-optimal designs for the logistic model

We propose an algorithm for constructing minimax D-optimal designs for the logistic model when only the ranges of the values for both parameters are assumed known. Properties of these designs are studied and compared with optimal Bayesian designs and Sitter's (1992, Biometrics, 48, 1145-1155) minimax D-optimal kk-designs. Examples of minimax D-optimal designs are presented for the logistic and power logistic models, including a dose-response design for rheumatoid arthritis patients.