The full Bayesian significance test for mixture models: results in gene expression clustering

Gene clustering is a useful exploratory technique to group together genes with similar expression levels under distinct cell cycle phases or distinct conditions. It helps the biologist to identify potentially meaningful relationships between genes. In this study, we propose a clustering method based on multivariate normal mixture models, where the number of clusters is predicted via sequential hypothesis tests: at each step, the method considers a mixture model of m components (m = 2 in the first step) and tests if in fact it should be m - 1. If the hypothesis is rejected, m is increased and a new test is carried out. The method continues (increasing m) until the hypothesis is accepted. The theoretical core of the method is the full Bayesian significance test, an intuitive Bayesian approach, which needs no model complexity penalization nor positive probabilities for sharp hypotheses. Numerical experiments were based on a cDNA microarray dataset consisting of expression levels of 205 genes belonging to four functional categories, for 10 distinct strains of Saccharomyces cerevisiae. To analyze the method's sensitivity to data dimension, we performed principal components analysis on the original dataset and predicted the number of classes using 2 to 10 principal components. Compared to Mclust (model-based clustering), our method shows more consistent results.

Cointegration: Bayesian Significance Test

To estimate causal relationships, time series econometricians must be aware of spurious correlation, a problem first mentioned by Yule (1926). To deal with this problem, one can work either with differenced series or multivariate models: VAR (VEC or VECM) models. These models usually include at least one cointegration relation. Although the Bayesian literature on VAR/VEC is quite advanced, Bauwens et al. (1999) highlighted that "the topic of selecting the cointegrating rank has not yet given very useful and convincing results". The present article applies the Full Bayesian Significance Test (FBST), especially designed to deal with sharp hypotheses, to cointegration rank selection tests in VECM time series models. It shows the FBST implementation using both simulated and available (in the literature) data sets. As illustration, standard non informative priors are used.

Disequilibrium Coefficient: A Bayesian Perspective

Hardy-Weinberg Equilibrium (HWE) is an important genetic property that populations should have whenever they are not observing adverse situations as complete lack of panmixia, excess of mutations, excess of selection pressure, etc. HWE for decades has been evaluated; both frequentist and Bayesian methods are in use today. While historically the HWE formula was developed to examine the transmission of alleles in a population from one generation to the next, use of HWE concepts has expanded in human diseases studies to detect genotyping error and disease susceptibility (association); Ryckman and Williams (2008). Most analyses focus on trying to answer the question of whether a population is in HWE. They do not try to quantify how far from the equilibrium the population is. In this paper, we propose the use of a simple disequilibrium coefficient to a locus with two alleles. Based on the posterior density of this disequilibrium coefficient, we show how one can conduct a Bayesian analysis to verify how far from HWE a population is. There are other coefficients introduced in the literature and the advantage of the one introduced in this paper is the fact that, just like the standard correlation coefficients, its range is bounded and it is symmetric around zero (equilibrium) when comparing the positive and the negative values. To test the hypothesis of equilibrium, we use a simple Bayesian significance test, the Full Bayesian Significance Test (FBST); see Pereira, Stern andWechsler (2008) for a complete review. The disequilibrium coefficient proposed provides an easy and efficient way to make the analyses, especially if one uses Bayesian statistics. A routine in R programs (R Development Core Team, 2009) that implements the calculations is provided for the readers.

Testing allele homogeneity: the problem of nested hypotheses

Background: The evaluation of associations between genotypes and diseases in a case-control framework plays an important role in genetic epidemiology. This paper focuses on the evaluation of the homogeneity of both genotypic and allelic frequencies. The traditional test that is used to check allelic homogeneity is known to be valid only under Hardy-Weinberg equilibrium, a property that may not hold in practice. Results: We first describe the flaws of the traditional (chi-squared) tests for both allelic and genotypic homogeneity. Besides the known problem of the allelic procedure, we show that whenever these tests are used, an incoherence may arise: sometimes the genotypic homogeneity hypothesis is not rejected, but the allelic hypothesis is. As we argue, this is logically impossible. Some methods that were recently proposed implicitly rely on the idea that this does not happen. In an attempt to correct this incoherence, we describe an alternative frequentist approach that is appropriate even when Hardy-Weinberg equilibrium does not hold. It is then shown that the problem remains and is intrinsic of frequentist procedures. Finally, we introduce the Full Bayesian Significance Test to test both hypotheses and prove that the incoherence cannot happen with these new tests. To illustrate this, all five tests are applied to real and simulated datasets. Using the celebrated power analysis, we show that the Bayesian method is comparable to the frequentist one and has the advantage of being coherent. Conclusions: Contrary to more traditional approaches, the Full Bayesian Significance Test for association studies provides a simple, coherent and powerful tool for detecting associations.

Significance tests in climate science

A large fraction of papers in the climate literature includes erroneous uses of significance tests. A Bayesian analysis is presented to highlight the meaning of significance tests and why typical misuse occurs. The significance statistic is not a quantitative measure of how confident we can be of the ‘reality’ of a given result. It is concluded that a significance test very rarely provides useful quantitative information.

Probing three-way interactions in moderated multiple regression:Development and application of a slope difference test

Researchers often use 3-way interactions in moderated multiple regression analysis to test the joint effect of 3 independent variables on a dependent variable. However, further probing of significant interaction terms varies considerably and is sometimes error prone. The authors developed a significance test for slope differences in 3-way interactions and illustrate its importance for testing psychological hypotheses. Monte Carlo simulations revealed that sample size, magnitude of the slope difference, and data reliability affected test power. Application of the test to published data yielded detection of some slope differences that were undetected by alternative probing techniques and led to changes of results and conclusions. The authors conclude by discussing the test's applicability for psychological research. Copyright 2006 by the American Psychological Association.

Teste de banco : adequação da altura do ergometro a estatura, para individuos a partir de 09 anos de idade, de ambosos sexos, praticantes e não praticantes de atividade fisica

Universidade Estadual de Campinas. Faculdade de Educação Física

Chemical evolution of the Galactic bulge as traced by microlensed dwarf and subgiant stars IV. Two bulge populations

Based on high-resolution (R approximate to 42 000 to 48 000) and high signal-to-noise (S/N approximate to 50 to 150) spectra obtained with UVES/VLT, we present detailed elemental abundances (O, Na, Mg, Al, Si, Ca, Ti, Cr, Fe, Ni, Zn, Y, and Ba) and stellar ages for 12 new microlensed dwarf and subgiant stars in the Galactic bulge. Including previous microlensing events, the sample of homogeneously analysed bulge dwarfs has now grown to 26. The analysis is based on equivalent width measurements and standard 1-D LTE MARCS model stellar atmospheres. We also present NLTE Li abundances based on line synthesis of the (7)Li line at 670.8 nm. The results from the 26 microlensed dwarf and subgiant stars show that the bulge metallicity distribution (MDF) is double-peaked; one peak at [Fe/H] approximate to -0.6 and one at [Fe/H] approximate to +0.3, and with a dearth of stars around solar metallicity. This is in contrast to the MDF derived from red giants in Baade's window, which peaks at this exact value. A simple significance test shows that it is extremely unlikely to have such a gap in the microlensed dwarf star MDF if the dwarf stars are drawn from the giant star MDF. To resolve this issue we discuss several possibilities, but we can not settle on a conclusive solution for the observed differences. We further find that the metal-poor bulge dwarf stars are predominantly old with ages greater than 10 Gyr, while the metal-rich bulge dwarf stars show a wide range of ages. The metal-poor bulge sample is very similar to the Galactic thick disk in terms of average metallicity, elemental abundance trends, and stellar ages. Speculatively, the metal-rich bulge population might be the manifestation of the inner thin disk. If so, the two bulge populations could support the recent findings, based on kinematics, that there are no signatures of a classical bulge and that the Milky Way is a pure-disk galaxy. Also, recent claims of a flat IMF in the bulge based on the MDF of giant stars may have to be revised based on the MDF and abundance trends probed by our microlensed dwarf stars.

SAKWeb – Spatial autocorrelation and kriging web, a W3 geocomputation perspective

A thesis submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Information Systems

Elaboração e estruturação de um modelo de rating interno

Temos vindo a assistir nos últimos anos a uma evolução no que respeita à avaliação do risco de crédito. As constantes alterações de regulamentação bancária, que resultam dos Acordos de Basileia, têm vindo a impor novas normas que condicionam a quantidade e a qualidade do risco de crédito que as Instituições de Crédito podem assumir nos seus balanços. É de grande importância as Instituições de Crédito avaliarem o risco de crédito, as garantias e o custo de capital, pois têm um impacto direto na sua gestão nomeadamente quanto à afetação de recursos e proteção contra perdas. Desta forma, pretende-se com o presente trabalho elaborar e estruturar um modelo de rating interno através de técnicas estatísticas, assim como identificar as variáveis estatisticamente relevantes no modelo considerado. Foi delineada uma metodologia de investigação mista, considerando na primeira parte do trabalho uma pesquisa qualitativa e na segunda parte uma abordagem quantitativa. Através da análise documental, fez-se uma abordagem dos conceitos teóricos e da regulamentação que serve de base ao presente trabalho. No estudo de caso, o modelo de rating interno foi desenvolvido utilizando a técnica estatística designada de regressão linear múltipla. A amostra considerada foi obtida através da base de dados SABI e é constituída por cem empresas solventes, situadas na zona de Paredes, num horizonte temporal de 2011-2013. A nossa análise baseou-se em três cenários, correspondendo cada cenário aos dados de cada ano (2011, 2012 e 2013). Para validar os pressupostos do modelo foram efetuados testes estatísticos de Durbin Watson e o teste de significância - F (ANOVA). Por fim, para obtermos a classificação de rating de cada variável foi aplicada a técnica dos percentis. Pela análise dos três cenários considerados, verificou-se que o cenário dois foi o que obteve maior coeficiente de determinação. Verificou-se ainda que as variáveis independentes, rácio de liquidez geral, grau de cobertura do ativo total pelo fundo de maneio e rácio de endividamento global são estatisticamente relevantes.

Análise do sistema bancário da União Europeia

Dissertação de mestrado em Economia Monetária, Bancária e Financeira

Histomorphometric Evaluation of Bioceramic Molecular Impregnated and Dual Acid-Etched Implant Surfaces in the Human Posterior Maxilla

Background: Physical and bioceramic incorporation surface treatments at the nanometer scale showed higher means of bone-to-implant contact (BIC) and torque values compared with surface topography at the micrometer scale; however, the literature concerning the effect of nanometer scale parameters is sparse. Purpose: The aim of this study was to evaluate the influence of two different implant surfaces on the percentage bone-to-implant contact (BIC%) and bone osteocyte density in the human posterior maxilla after 2 months of unloaded healing. Materials and Methods: The implants utilized presented dual acid-etched (DAE) surface and a bioceramic molecular impregnated treatment (Ossean(R), Intra-Lock International, Boca Raton, FL, USA) serving as control and test, respectively. Ten subjects (59 1 9 years of age) received two implants (one of each surface) during conventional implant surgery in the posterior maxilla. After the non-loaded period of 2 months, the implants and the surrounding tissue were removed by means of a trephine and were non-decalcified processed for ground sectioning and analysis of BIC%, bone density in threaded area (BA%), and osteocyte index (Oi). Results: Two DAE implants were found to be clinically unstable at time of retrieval. Histometric evaluation showed significantly higher BIC% and Oi for the test compared to the control surface (p < .05), and that BA% was not significantly different between groups. Wilcoxon matched pairs test was used to compare the differences of histomorphometric variables between implant surfaces. The significance test was conducted at a 5% level of significance. Conclusion: The histological data suggest that the bioceramic molecular impregnated surface-treated implants positively modulated bone healing at early implantation times compared to the DAE surface.

Cutpoint selection for discretizing a continuous covariate for generalized estimating equations

We consider consider the problem of dichotomizing a continuous covariate when performing a regression analysis based on a generalized estimation approach. The problem involves estimation of the cutpoint for the covariate and testing the hypothesis that the binary covariate constructed from the continuous covariate has a significant impact on the outcome. Due to the multiple testing used to find the optimal cutpoint, we need to make an adjustment to the usual significance test to preserve the type-I error rates. We illustrate the techniques on one data set of patients given unrelated hematopoietic stem cell transplantation. Here the question is whether the CD34 cell dose given to patient affects the outcome of the transplant and what is the smallest cell dose which is needed for good outcomes. (C) 2010 Elsevier BM. All rights reserved.

Early Onset Obsessive-Compulsive Disorder With and Without Tics

Introduction: Research suggests that obsessive-compulsive disorder (OCD) is not a unitary entity, but rather a highly heterogeneous condition, with complex and variable clinical manifestations. Objective: The aims of this study were to compare clinical and demographic characteristics of OCD patients with early and late age of onset of obsessive-compulsive symptoms (OCS); and to compare the same features in early onset OCD with and without tics. The independent impact of age at onset and presence of tics on comorbidity patterns was investigated. Methods: Three hundred and thirty consecutive outpatients meeting Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria for OCD were evaluated: 160 patients belonged to the ""early onset"" group (EOG): before 11 years of age, 75 patients had an ""intermediate onset"" (IOG), and 95 patients were from the ""late onset"" group (LOG): after 18 years of age. From the 160 EOG, 60 had comorbidity with tic disorders. The diagnostic instruments used were: the Yale-Brown Obsessive Compulsive Scale and the Dimensional Yale-Brown Obsessive Compulsive Scale (DY-BOCS), Yale Global Tics Severity Scale; and Structured Clinical Interview for DSM-IV Axis I Disorders-patient edition. Statistical tests used were: Mann-Whitney, full Bayesian significance test, and logistic regression. Results: The EOG had a predominance of males, higher frequency of family history of OCS, higher mean scores on the ""aggression/violence"" and ""miscellaneous"" dimensions, and higher mean global DY-BOCS scores. Patients with EOG without tic disorders presented higher mean global DY-BOCS scores and higher mean scores in the ""contamination/cleaning"" dimension. Conclusion: The current results disentangle some of the clinical overlap between early onset OCD with and without tics. CNS Spectr. 2009; 14(7):362-370

Funções de pedotransferência para a curva de resistência do solo à penetração

A estimativa da curva de resistência do solo à penetração (CRP) a partir de variáveis de fácil obtenção, como o conteúdo de água, representa uma medida útil não só para a quantificação do estado de compactação, mas também para facilitar a interpretação da resistência do solo à penetração obtida em diferentes condições de campo. O objetivo deste trabalho foi estimar a CRP em solos de diferentes granulometrias e densidades, a partir de dados obtidos com o penetrômetro de impacto. O experimento foi realizado no laboratório de Pedologia da Faculdade de Ciências Agrárias e Veterinárias (UNESP), Jaboticabal, SP. Foram utilizadas quatro classes de solos: Neossolo Quartzarênico, Argissolo Vermelho-Amarelo, Latossolo Vermelho distrófico e Latossolo Vermelho acriférrico, os quais foram coletados na camada de 0-0,20 m. Colunas de PVC, com dimensões de 0,25 m de diâmetro e 0,6 m de altura, foram preenchidas de forma a obter duas condições de compactação: menor densidade e maior densidade do solo. O conteúdo de água nos solos, inicialmente elevado até o ponto de saturação, foi monitorado diariamente por meio de um medidor eletrônico tipo TDR (Profile Probe PR2 acoplado ao Moisture Meter HH2). A resistência do solo à penetração foi mensurada por meio de um penetrômetro de impacto adaptado para vaso. Os pares de dados entre a resistência do solo à penetração e o conteúdo de água foram ajustados, e as CRP foram submetidas ao teste de significância. A relação entre a resistência do solo à penetração e o conteúdo de água foi descrita pelo modelo exponencial decrescente: em que RP representa a resistência do solo à penetração (MPa); Ug é o conteúdo de água (kg kg-1); e A, B e C são os coeficientes da equação. Foram obtidos coeficientes de determinação que variaram de 0,79 a 0,96.