Analysis of Crossover Designs with a Categorical Response

In the analysis of two-period crossover designs, one frequently must consider the case of a categorical response with binary as a special case. These circumstances are considered in this paper and the proposed method—an extension of GART'S tests for the binary case—is similar to that of PIKE, CASAGRANDE and SMITH for the analysis of pair-matched case-control studies. The results are illustrated with a numerical example.     

On Construction of Some Augmented Block Designs

Augmented block designs are frequently used in practice. In this paper procedures of construction of some types of augmented block designs are discussed using the concept of efficiency-balance and partially efficiency-balance.     

On the analysis of phylogenetically paired designs

As phylogenetically controlled experimental designs become increasingly common in ecology, the need arises for a standardized statistical treatment of these datasets. Phylogenetically paired designs circumvent the need for resolved phylogenies and have been used to compare species groups, particularly in the areas of invasion biology and adaptation. Despite the widespread use of this approach, the statistical analysis of paired designs has not been critically evaluated. We propose a mixed model approach that includes random effects for pair and species. These random effects introduce a “two-layer” compound symmetry variance structure that captures both the correlations between observations on related species within a pair as well as the correlations between the repeated measurements within species. We conducted a simulation study to assess the effect of model misspecification on Type I and II error rates. We also provide an illustrative example with data containing taxonomically similar species and several outcome variables of interest. We found that a mixed model with species and pair as random effects performed better in these phylogenetically explicit simulations than two commonly used reference models (no or single random effect) by optimizing Type I error rates and power. The proposed mixed model produces acceptable Type I and II error rates despite the absence of a phylogenetic tree. This design can be generalized to a variety of datasets to analyze repeated measurements in clusters of related subjects/species.     

Genetic counselling for pulmonary arterial hypertension: a matter of variable variability

We report three cases which highlight the complex considerations surrounding genetic counselling for pulmonary arterial hypertension (PAH). The first counselee developed PAH symptoms shortly after his daughter’s death from PAH and was diagnosed with a delay of 1 year. An early diagnosis of familial PAH was established in the second counselee. Oral therapy was initiated immediately, and her functional status has since remained stable. The third counselee was a healthy woman who struggled to cope with her risk for familial PAH, having lost two siblings from the disease. These cases show that incomplete penetrance and variable expression need particular attention during clinical assessment and genetic counselling of heritable PAH patients and family members.     

A response-adaptive randomization procedure for multi-armed clinical trials with normally distributed outcomes

We propose a novel response-adaptive randomization procedure for multi-armed trials with continuous outcomes that are assumed to be normally distributed. Our proposed rule is non-myopic, and oriented toward a patient benefit objective, yet maintains computational feasibility. We derive our response-adaptive algorithm based on the Gittins index for the multi-armed bandit problem, as a modification of the method first introduced in Villar et al. (Biometrics, 71, pp. 969-978). The resulting procedure can be implemented under the assumption of both known or unknown variance. We illustrate the proposed procedure by simulations in the context of phase II cancer trials. Our results show that, in a multi-armed setting, there are efficiency and patient benefit gains of using a response-adaptive allocation procedure with a continuous endpoint instead of a binary one. These gains persist even if an anticipated low rate of missing data due to deaths, dropouts, or complete responses is imputed online through a procedure first introduced in this paper. Additionally, we discuss how there are response-adaptive designs that outperform the traditional equal randomized design both in terms of efficiency and patient benefit measures in the multi-armed trial context.     

Augmented p-rep designs

Early generation variety trials are very important in plant and tree breeding programs. Typically many entries are tested, often with very little resources available. Unreplicated trials using control plots are popular and it is common to repeat the trials at a number of locations. An alternative is to use p-rep designs, where a proportion of the test entries are replicated at each location; this can obviate the need for control plots. α-Designs are commonly used for replicated variety trials and we show how these can be adapted to produce efficient p-rep designs.     

Exact Tests for Comparing Two Paired Proportions with Incomplete Data

Various asymptotic test procedures have been developed previously for testing the equality of two binomial proportions with partially incomplete paired data. Test procedures that discard incomplete observations have been shown to be less powerful than those procedures that utilize all available observations. On the other hand, asymptotic test procedures that utilize all available observations may not be reliable in small‐sample problems or sparse data structures. In this article, unconditional exact test procedures are proposed for testing the equality of two paired binomial proportions with partially incomplete paired data under a random mechanism. The proposed unconditional exact test methods are illustrated with real data from a neurological study. Empirical studies are conducted to investigate the performance of these and other test procedures with respect to size and power. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Characteristics of the optimum combination of synthetic soils by plant and soil properties used for rock slope restoration

Bare rock slopes often deteriorate microclimates and drive water erosion and landslides. Moreover, they impose hidden troubles on humans and have increasingly been brought to the attention of the public. In order to optimize synthetic soils (SS) for improving the outside soil spray seeding (OSSS) technique used for the restoration of rock slopes, we investigated physico-chemical properties and plant growth of a series of SS designed with orthogonal array OA₂₅ (5⁵). Five additive components, cement, inorganic compound fertilizers, peat soil, wood chip and water–absorbent polymers at five levels, were applied to optimize the synthetic soils. In the present study, we only investigated the effects of a single additive component on all the indicators measured. Primarily, results showed that the contributions of cement to plant biomass, pH and water holding content; the contributions of inorganic compound fertilizers to plant biomass and total nitrogen, available nitrogen, total phosphorus and available phosphorus; the contributions of both peat soil and wood chip to plant biomass, water holding content and organic carbon; and the contributions of water absorbent polymers to the plant biomass, water holding content and available nitrogen were all significant. According to the plant growth and physico-chemical properties of the synthetic soils, Treatment-12 consisting of 1.5% cement, 0.4% inorganic compound fertilizers, 1.5% peat soil, 0.3% water absorbent agent and 2.0% wood chip, was the optimum combination among the 25 treatments for the restoration of rock slopes. The properties of the optimized SS to support growth of plants and to resist erosion were verified by an experiment using an actual rock slope.     

基因流介导的种间渐渗与物种界定

物种界定是生物学中最基本的问题之一。近年来随着分子生物学技术的进步如分子条形码的发展,物种界定也越来越引起人们的兴趣。界定一个物种或相似的一组物种时最重要的一个原则就是选择适合的分子标记。然而,植物中广泛存在的不完全谱系筛选与种间渐渗却常常会阻碍准确鉴定物种。最近,有关基因流介导的种间渗入和物种界定在理论和实验研究中都取得了重大进展。本文综述了基因流介导的物种形成;评价了种间渐渗与不完全谱系筛选的区别;最后总结出应该利用基因流速度较快的分子标记去鉴定物种。     

Effective correction of experimental errors in quantitative proteomics using stable isotope labeling by amino acids in cell culture (SILAC)

Accurate and reliable quantitative proteomics in cell culture has been considerably facilitated by the introduction of the stable isotope labeling by amino acids in cell culture (SILAC), combined with high resolution mass spectrometry. There are however several major sources of quantification errors that commonly occur with SILAC techniques, i.e. incomplete incorporation of isotopic amino acids, arginine-to-proline conversion, and experimental errors in final sample mixing. Dataset normalization is a widely adopted solution to such errors, however this may not completely prevent introducing incorrect expression ratios. Here we demonstrate that a label-swap replication of SILAC experiments was able to effectively correct experimental errors by averaging ratios measured in individual replicates using quantitative proteomics and phosphoproteomics of ligand treatment of neural cell cultures. Furthermore, this strategy was successfully applied to a SILAC triplet experiment, which presents a much more complicated experimental matrix, affected by both incomplete labeling and arginine-to-proline conversion. Based on our results, we suggest that SILAC experiments should be designed to incorporate label-swap replications for enhanced reliability in expression ratios.