Bridging the gap between different statistical approaches: An integrated framework for modelling

This paper proposes a template for modelling complex datasets that integrates traditional statistical modelling approaches with more recent advances in statistics and modelling through an exploratory framework. Our approach builds on the well-known and long standing traditional idea of 'good practice in statistics' by establishing a comprehensive framework for modelling that focuses on exploration, prediction, interpretation and reliability assessment, a relatively new idea that allows individual assessment of predictions. The integrated framework we present comprises two stages. The first involves the use of exploratory methods to help visually understand the data and identify a parsimonious set of explanatory variables. The second encompasses a two step modelling process, where the use of non-parametric methods such as decision trees and generalized additive models are promoted to identify important variables and their modelling relationship with the response before a final predictive model is considered. We focus on fitting the predictive model using parametric, non-parametric and Bayesian approaches. This paper is motivated by a medical problem where interest focuses on developing a risk stratification system for morbidity of 1,710 cardiac patients given a suite of demographic, clinical and preoperative variables. Although the methods we use are applied specifically to this case study, these methods can be applied across any field, irrespective of the type of response.

Bayesian sample size for exploratory clinical trials incorporating historical data

This paper presents a simple Bayesian approach to sample size determination in clinical trials. It is required that the trial should be large enough to ensure that the data collected will provide convincing evidence either that an experimental treatment is better than a control or that it fails to improve upon control by some clinically relevant difference. The method resembles standard frequentist formulations of the problem, and indeed in certain circumstances involving 'non-informative' prior information it leads to identical answers. In particular, unlike many Bayesian approaches to sample size determination, use is made of an alternative hypothesis that an experimental treatment is better than a control treatment by some specified magnitude. The approach is introduced in the context of testing whether a single stream of binary observations are consistent with a given success rate p(0). Next the case of comparing two independent streams of normally distributed responses is considered, first under the assumption that their common variance is known and then for unknown variance. Finally, the more general situation in which a large sample is to be collected and analysed according to the asymptotic properties of the score statistic is explored. Copyright (C) 2007 John Wiley & Sons, Ltd.

Bayesian design and conduct of phase II single-arm clinical trials with binary outcomes: a tutorial

The aim of phase II single-arm clinical trials of a new drug is to determine whether it has sufficient promising activity to warrant its further development. For the last several years Bayesian statistical methods have been proposed and used. Bayesian approaches are ideal for earlier phase trials as they take into account information that accrues during a trial. Predictive probabilities are then updated and so become more accurate as the trial progresses. Suitable priors can act as pseudo samples, which make small sample clinical trials more informative. Thus patients have better chances to receive better treatments. The goal of this paper is to provide a tutorial for statisticians who use Bayesian methods for the first time or investigators who have some statistical background. In addition, real data from three clinical trials are presented as examples to illustrate how to conduct a Bayesian approach for phase II single-arm clinical trials with binary outcomes.

The Bayesian revolution in genetics

Bayesian statistics allow scientists to easily incorporate prior knowledge into their data analysis. Nonetheless, the sheer amount of computational power that is required for Bayesian statistical analyses has previously limited their use in genetics. These computational constraints have now largely been overcome and the underlying advantages of Bayesian approaches are putting them at the forefront of genetic data analysis in an increasing number of areas.

A Bayesian approach to estimating the regression coefficients of a multinomial logit model

A Bayesian approach to estimation of the regression coefficients of a multinominal logit model with ordinal scale response categories is presented. A Monte Carlo method is used to construct the posterior distribution of the link function. The link function is treated as an arbitrary scalar function. Then the Gauss-Markov theorem is used to determine a function of the link which produces a random vector of coefficients. The posterior distribution of the random vector of coefficients is used to estimate the regression coefficients. The method described is referred to as a Bayesian generalized least square (BGLS) analysis. Two cases involving multinominal logit models are described. Case I involves a cumulative logit model and Case II involves a proportional-odds model. All inferences about the coefficients for both cases are described in terms of the posterior distribution of the regression coefficients. The results from the BGLS method are compared to maximum likelihood estimates of the regression coefficients. The BGLS method avoids the nonlinear problems encountered when estimating the regression coefficients of a generalized linear model. The method is not complex or computationally intensive. The BGLS method offers several advantages over Bayesian approaches. ^

Bayesian adaptive designs in early phase clinical trials

There are two practical challenges in the phase I clinical trial conduct: lack of transparency to physicians, and the late onset toxicity. In my dissertation, Bayesian approaches are used to address these two problems in clinical trial designs. The proposed simple optimal designs cast the dose finding problem as a decision making process for dose escalation and deescalation. The proposed designs minimize the incorrect decision error rate to find the maximum tolerated dose (MTD). For the late onset toxicity problem, a Bayesian adaptive dose-finding design for drug combination is proposed. The dose-toxicity relationship is modeled using the Finney model. The unobserved delayed toxicity outcomes are treated as missing data and Bayesian data augment is employed to handle the resulting missing data. Extensive simulation studies have been conducted to examine the operating characteristics of the proposed designs and demonstrated the designs' good performances in various practical scenarios.^

Molecular analysis of the dengue virus type 1 and 2 in Brazil based on sequences of the genomic envelope-nonstructural protein 1 junction region

The genomic sequences of the Envelope-Non-Structural protein 1 junction region (E/NS1) of 84 DEN-1 and 22 DEN-2 isolates from Brazil were determined. Most of these strains were isolated in the period from 1995 to 2001 in endemic and regions of recent dengue transmission in São Paulo State. Sequence data for DEN-1 and DEN-2 utilized in phylogenetic and split decomposition analyses also include sequences deposited in GenBank from different regions of Brazil and of the world. Phylogenetic analyses were done using both maximum likelihood and Bayesian approaches. Results for both DEN-1 and DEN-2 data are ambiguous, and support for most tree bipartitions are generally poor, suggesting that E/NS1 region does not contain enough information for recovering phylogenetic relationships among DEN-1 and DEN-2 sequences used in this study. The network graph generated in the split decomposition analysis of DEN-1 does not show evidence of grouping sequences according to country, region and clades. While the network for DEN-2 also shows ambiguities among DEN-2 sequences, it suggests that Brazilian sequences may belong to distinct subtypes of genotype III.

Antiretroviral activity of ancestral TRIM5alpha.

The antiretroviral protein TRIM5alpha is known to have evolved different restriction capacities against various retroviruses, driven by positive Darwinian selection. However, how these different specificities have evolved in the primate lineages is not fully understood. Here we used ancestral protein resurrection to estimate the evolution of antiviral restriction specificities of TRIM5alpha on the primate lineage leading to humans. We used TRIM5alpha coding sequences from 24 primates for the reconstruction of ancestral TRIM5alpha sequences using maximum-likelihood and Bayesian approaches. Ancestral sequences were transduced into HeLa and CRFK cells. Stable cell lines were generated and used to test restriction of a panel of extant retroviruses (human immunodeficiency virus type 1 [HIV-1] and HIV-2, simian immunodeficiency virus [SIV] variants SIV(mac) and SIV(agm), and murine leukemia virus [MLV] variants N-MLV and B-MLV). The resurrected TRIM5alpha variant from the common ancestor of Old World primates (Old World monkeys and apes, approximately 25 million years before present) was effective against present day HIV-1. In contrast to the HIV-1 restriction pattern, we show that the restriction efficacy against other retroviruses, such as a murine oncoretrovirus (N-MLV), is higher for more recent resurrected hominoid variants. Ancestral TRIM5alpha variants have generally limited efficacy against HIV-2, SIV(agm), and SIV(mac). Our study sheds new light on the evolution of the intrinsic antiviral defense machinery and illustrates the utility of functional evolutionary reconstruction for characterizing recently emerged protein differences.

Comparative phylogeography of mutualists and the effect of the host on the genetic structure of its partners.

Whether or not species participating in specialized and obligate interactions display similar and simultaneous demographic variations at the intraspecific level remains an open question in phylogeography. In the present study, we used the mutualistic nursery pollination occurring between the European globeflower Trollius europaeus and its specialized pollinators in the genus Chiastocheta as a case study. Explicitly, we investigated if the phylogeographies of the pollinating flies are significantly different from the expectation under a scenario of plant-insect congruence. Based on a large-scale sampling, we first used mitochondrial data to infer the phylogeographical histories of each fly species. Then, we defined phylogeographical scenarios of congruence with the plant history, and used maximum likelihood and Bayesian approaches to test for plant-insect phylogeographical congruence for the three Chiastocheta species. We show that the phylogeographical histories of the three fly species differ. Only Chiastocheta lophota and Chiastocheta dentifera display strong spatial genetic structures, which do not appear to be statistically different from those expected under scenarios of phylogeographical congruence with the plant. The results of the present study indicate that the fly species responded in independent and different ways to shared evolutionary forces, displaying varying levels of congruence with the plant genetic structure

Effects of a fire response trait on diversification in replicated radiations.

Fire has been proposed as a factor explaining the exceptional plant species richness found in Mediterranean regions. A fire response trait that allows plants to cope with frequent fire by either reseeding or resprouting could differentially affect rates of species diversification. However, little is known about the generality of the effects of differing fire response on species evolution. We study this question in the Restionaceae, a family that radiated in Southern Africa and Australia. These radiations occurred independently and represent evolutionary replicates. We apply Bayesian approaches to estimate trait-specific diversification rates and patterns of climatic niche evolution. We also compare the climatic heterogeneity of South Africa and Australia. Reseeders diversify faster than resprouters in South Africa, but not in Australia. We show that climatic preferences evolve more rapidly in reseeder lineages than in resprouters and that the optima of these climatic preferences differ between the two strategies. We find that South Africa is more climatically heterogeneous than Australia, independent of the spatial scale we consider. We propose that rapid shifts between states of the fire response trait promote speciation by separating species ecologically, but this only happens when the landscape is sufficiently heterogeneous.

Delineamentos experimentais eficientes para estudos de cinética química

In this paper we show how to obtain efficient designs of experiments for fitting Michaelis-Menten and Hill equations useful in chemical studies. The search of exact D-optimal designs by using local and pseudo-Bayesian approaches is considered. Optimal designs were compared to those commonly used in practice using an efficiency measure and theoretical standard errors of the kinetic parameter estimates. In conclusion, the D-optimal designs based on the Hill equation proved efficient for estimating the parameters of both models. Furthermore, these are promising with respect to practical issues, allowing efficient estimation as well as goodness-of-fit tests and comparisons between some kinetic models.

Phylogénie moléculaire du genre Salix L. (Salicaceae) en Amérique du Nord

La culture de saules (Salix sp.) est une pratique courante en Europe et en Amérique du Nord pour produire de la biomasse végétale. Cependant, le développement d’outils moléculaires est très récent. De plus, la phylogénie des saules est incomplète. Il y a un manque d’information pour les programmes de sélection d'espèces indigènes et pour la compréhension de l’évolution du genre. Le genre Salix inclut 500 espèces réparties principalement dans les régions tempérées et boréo-arctique de l’hémisphère nord. Nous avons obtenu l’ensemble des espèces retrouvées naturellement en Amérique (121 indigènes et introduites). Dans un premier temps, nous avons développé de nouveaux outils moléculaires et méthodes : extraction d’ADN, marqueurs microsatellites et gènes nucléaires. Puis, nous avons séquencé deux gènes chloroplastiques (matK et rbcL) et la région ITS. Les analyses phylogénétiques ont été réalisées selon trois approches : parcimonie, maximum de vraisemblance et Bayésienne. L’arbre d’espèces obtenu a un fort support et divise le genre Salix en deux sous-genres, Salix et Vetrix. Seize espèces ont une position ambiguë. La diversité génétique du sous-genre Vetrix est plus faible. Une phylogénie moléculaire complète a été établie pour les espèces américaines. D’autres analyses et marqueurs sont nécessaires pour déterminer les relations phylogénétiques entre certaines espèces. Nous affirmons que le genre Salix est divisé en deux clades.

An illustration of the modelling of cost and efficacy data from a clinical trial

Health care providers, purchasers and policy makers need to make informed decisions regarding the provision of cost-effective care. When a new health care intervention is to be compared with the current standard, an economic evaluation alongside an evaluation of health benefits provides useful information for the decision making process. We consider the information on cost-effectiveness which arises from an individual clinical trial comparing the two interventions. Recent methods for conducting a cost-effectiveness analysis for a clinical trial have focused on the net benefit parameter. The net benefit parameter, a function of costs and health benefits, is positive if the new intervention is cost-effective compared with the standard. In this paper we describe frequentist and Bayesian approaches to cost-effectiveness analysis which have been suggested in the literature and apply them to data from a clinical trial comparing laparoscopic surgery with open mesh surgery for the repair of inguinal hernias. We extend the Bayesian model to allow the total cost to be divided into a number of different components. The advantages and disadvantages of the different approaches are discussed. In January 2001, NICE issued guidance on the type of surgery to be used for inguinal hernia repair. We discuss our example in the light of this information. Copyright © 2003 John Wiley & Sons, Ltd.