Regression Models with Heteroscedasticity using Bayesian Approach

In this paper, we compare the performance of two statistical approaches for the analysis of data obtained from the social research area. In the first approach, we use normal models with joint regression modelling for the mean and for the variance heterogeneity. In the second approach, we use hierarchical models. In the first case, individual and social variables are included in the regression modelling for the mean and for the variance, as explanatory variables, while in the second case, the variance at level 1 of the hierarchical model depends on the individuals (age of the individuals), and in the level 2 of the hierarchical model, the variance is assumed to change according to socioeconomic stratum. Applying these methodologies, we analyze a Colombian tallness data set to find differences that can be explained by socioeconomic conditions. We also present some theoretical and empirical results concerning the two models. From this comparative study, we conclude that it is better to jointly modelling the mean and variance heterogeneity in all cases. We also observe that the convergence of the Gibbs sampling chain used in the Markov Chain Monte Carlo method for the jointly modeling the mean and variance heterogeneity is quickly achieved.

A flexible model for survival data with a cure rate: a Bayesian approach

In this paper we deal with a Bayesian analysis for right-censored survival data suitable for populations with a cure rate. We consider a cure rate model based on the negative binomial distribution, encompassing as a special case the promotion time cure model. Bayesian analysis is based on Markov chain Monte Carlo (MCMC) methods. We also present some discussion on model selection and an illustration with a real dataset.

Bayesian analysis for a skew extension of the multivariate null intercept measurement error model

Skew-normal distribution is a class of distributions that includes the normal distributions as a special case. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis in a multivariate, null intercept, measurement error model [R. Aoki, H. Bolfarine, J.A. Achcar, and D. Leao Pinto Jr, Bayesian analysis of a multivariate null intercept error-in -variables regression model, J. Biopharm. Stat. 13(4) (2003b), pp. 763-771] where the unobserved value of the covariate (latent variable) follows a skew-normal distribution. The results and methods are applied to a real dental clinical trial presented in [A. Hadgu and G. Koch, Application of generalized estimating equations to a dental randomized clinical trial, J. Biopharm. Stat. 9 (1999), pp. 161-178].

Inferential Implications of Over-Parametrization: A Case Study in Incomplete Categorical Data

P>In the context of either Bayesian or classical sensitivity analyses of over-parametrized models for incomplete categorical data, it is well known that prior-dependence on posterior inferences of nonidentifiable parameters or that too parsimonious over-parametrized models may lead to erroneous conclusions. Nevertheless, some authors either pay no attention to which parameters are nonidentifiable or do not appropriately account for possible prior-dependence. We review the literature on this topic and consider simple examples to emphasize that in both inferential frameworks, the subjective components can influence results in nontrivial ways, irrespectively of the sample size. Specifically, we show that prior distributions commonly regarded as slightly informative or noninformative may actually be too informative for nonidentifiable parameters, and that the choice of over-parametrized models may drastically impact the results, suggesting that a careful examination of their effects should be considered before drawing conclusions.Resume Que ce soit dans un cadre Bayesien ou classique, il est bien connu que la surparametrisation, dans les modeles pour donnees categorielles incompletes, peut conduire a des conclusions erronees. Cependant, certains auteurs persistent a negliger les problemes lies a la presence de parametres non identifies. Nous passons en revue la litterature dans ce domaine, et considerons quelques exemples surparametres simples dans lesquels les elements subjectifs influencent de facon non negligeable les resultats, independamment de la taille des echantillons. Plus precisement, nous montrons comment des a priori consideres comme peu ou non-informatifs peuvent se reveler extremement informatifs en ce qui concerne les parametres non identifies, et que le recours a des modeles surparametres peut avoir sur les conclusions finales un impact considerable. Ceci suggere un examen tres attentif de l`impact potentiel des a priori.

A Bayesian Semiparametric Approach for Solving the Discrete Calibration Problem

In this article, we introduce a semi-parametric Bayesian approach based on Dirichlet process priors for the discrete calibration problem in binomial regression models. An interesting topic is the dosimetry problem related to the dose-response model. A hierarchical formulation is provided so that a Markov chain Monte Carlo approach is developed. The methodology is applied to simulated and real data.

First study on the thermo-solvatochromism in aqueous 1-(1-butyl)-3-methylimidazolium tetrafluoroborate: A comparison between the solvation by an ionic liquid and by aqueous alcohols

The thermo-solvatochrornic behaviors of 2,6-diphenyl-4-(2,4,6-triphenylpyridinium-1-yl) phenolate, RB; 2,6-dichloro-4-(2,4,6-triphenyloyridinium-1-yl) phenolate, WB; 2,6-dibromo-4-[(E)-2-(1-methylpyridinium-4-yl)ethenyl] phenolate, MePMBr(2); 2,6-dibromo-4-[(E)-2-(1-n-octylpyridinium-4-yl)ethenyl] phenolate, OcPMBr(2), have been investigated in binary mixtures of the ionic liquid, IL, 1-(1-butyl)-3-methylimidazolium tetrafluorborate, [BuMeIm][BF(4)], and water (W), in the temperature range from 10 to 60 degrees C. Plots of the empirical solvent polarities, ET (probe) in kcal mol(-1), versus the mole fraction of water in the binary mixture, chi(w) showed nonlinear, i.e., nonideal behavior. Solvation by these IL-W mixtures shows the following similarities to that by aqueous aliphatic alcohols: The same solvation model can be conveniently employed to treat the data obtained; it is based on the presence in the system-bulk medium and probe solvation shell of IL, W, and the ""complex"" solvent 1:1 IL-W. The origin of the nonideal solvation behavior appears to be the same, preferential solvation of the probe, in particular by the complex solvent. The strength of association of the IL-W complex, and the polarity of the IL are situated between the corresponding values of aqueous methanol and aqueous ethanol. Temperature increase causes a gradual desolvation of all probes employed. A difference between solvation by IL-W and aqueous alcohols is that probe-solvent hydrophobic interactions appear to play a minor role in case of the former mixture, probably because solvation is dominated by hydrogen-bonding and Coulombic interactions between the ions of the IL and the zwitterionic probes.

Effect of the chain length in the structure of imidazolic ionic liquids and dimethylformamide solutions probed by Raman spectroscopy

The Raman band assigned to the nu(C=O)mode in N,N-dimethylformamide (at ca. 1660 cm(-1)) was used as a probe to study a group of ionic liquids 1-alkyl-3-methylimidazolium bromide ([C(n)Mlm]Br) with different alkyl groups (n = 2, 4, 6, 8 and 10 carbons) in binary equimolar binary mixtures with dimethylformamide. Due to the high electric dipole moment of the group C=O, there is a substantial coupling between adjacent molecules in the solution, and the corresponding Raman band involves both vibrational and reorientational modes. Different chain lengths of the ILs lead to different extents of the uncoupling of adjacent molecules of dimethylformamide, resulting in different shifts for this band in the mixtures. Information about the organization of ionic liquids in solution was obtained and a model of aggregation for these systems is proposed. (C) 2010 Elsevier B.V. All rights reserved.

Effect of propolis gel on the in vitro reduction of dentin permeability

OBJECTIVE: The aim of this study was to evaluate the capacity of potassium oxalate, fluoride gel and two kinds of propolis gel to reduce the hydraulic conductance of dentin, in vitro. MATERIAL AND METHODS: The methodology used for the measurement of hydraulic conductance of dentin in the present study was based on a model proposed in literature. Thirty-six 1-mm-thick dentin discs, obtained from extracted human third molars were divided into 4 groups (n=9). The groups corresponded to the following experimental materials: GI-10% propolis gel, pH 4.1; GII-30% propolis gel; GIII-3% potassium oxalate gel, pH 4,1; and GIV-1.23% fluoride gel, pH 4.1, applied to the dentin under the following surface conditions: after 37% phosphoric acid and before 6% citric acid application. The occluding capacity of the dentin tubules was evaluated using scanning electron microscopy (SEM) at ×500, ×1,000 and ×2,000 magnifications. Data were analyzed statistically by two-way ANOVA and Tukey's test at 5% significance level. RESULTS: Groups I, II, III, IV did not differ significantly from the others in any conditions by reducing in hydraulic conductance. The active agents reduced dentin permeability; however they produced the smallest reduction in hydraulic conductance when compared to the presence of smear layer (P<0.05). The effectiveness in reducing dentin permeability did not differ significantly from 10% or 30% propolis gels. SEM micrographs revealed that dentin tubules were partially occluded after treatment with propolis. CONCLUSIONS: Under the conditions of this study, the application of 10% and 30% propolis gels did not seem to reduce the hydraulic conductance of dentin in vitro, but it showed capacity of partially obliterating the dentin tubules. Propolis is used in the treatment of different oral problems without causing significant great collateral effects, and can be a good option in the treatment of patients with dentin sensitivity.

Validation of the Deardorff model for estimating energy balance components for a sugarcane crop

The quantification of the available energy in the environment is important because it determines photosynthesis, evapotranspiration and, therefore, the final yield of crops. Instruments for measuring the energy balance are costly and indirect estimation alternatives are desirable. This study assessed the Deardorff's model performance during a cycle of a sugarcane crop in Piracicaba, State of São Paulo, Brazil, in comparison to the aerodynamic method. This mechanistic model simulates the energy fluxes (sensible, latent heat and net radiation) at three levels (atmosphere, canopy and soil) using only air temperature, relative humidity and wind speed measured at a reference level above the canopy, crop leaf area index, and some pre-calibrated parameters (canopy albedo, soil emissivity, atmospheric transmissivity and hydrological characteristics of the soil). The analysis was made for different time scales, insolation conditions and seasons (spring, summer and autumn). Analyzing all data of 15 minute intervals, the model presented good performance for net radiation simulation in different insolations and seasons. The latent heat flux in the atmosphere and the sensible heat flux in the atmosphere did not present differences in comparison to data from the aerodynamic method during the autumn. The sensible heat flux in the soil was poorly simulated by the model due to the poor performance of the soil water balance method. The Deardorff's model improved in general the flux simulations in comparison to the aerodynamic method when more insolation was available in the environment.

Impact on human health of particulate matter emitted from burnings in the Brazilian Amazon region

OBJECTIVE: To analyze the impact on human health of exposure to particulate matter emitted from burnings in the Brazilian Amazon region. METHODS: This was an ecological study using an environmental exposure indicator presented as the percentage of annual hours (AH%) of PM2.5 above 80 μg/m3. The outcome variables were the rates of hospitalization due to respiratory disease among children, the elderly and the intermediate age group, and due to childbirth. Data were obtained from the National Space Research Institute and the Ministry of Health for all of the microregions of the Brazilian Amazon region, for the years 2004 and 2005. Multiple regression models for the outcome variables in relation to the predictive variable AH% of PM2.5 above 80 μg/m3 were analyzed. The Human Development Index (HDI) and mean number of complete blood counts per 100 inhabitants in the Brazilian Amazon region were the control variables in the regression analyses. RESULTS: The association of the exposure indicator (AH%) was higher for the elderly than for other age groups (β = 0.10). For each 1% increase in the exposure indicator there was an increase of 8% in child hospitalization, 10% in hospitalization of the elderly, and 5% for the intermediate age group, even after controlling for HDI and mean number of complete blood counts. No association was found between the AH% and hospitalization due to childbirth. CONCLUSIONS: The indicator of atmospheric pollution showed an association with occurrences of respiratory diseases in the Brazilian Amazon region, especially in the more vulnerable age groups. This indicator may be used to assess the effects of forest burning on human health.

Trypanosoma cruzi benznidazole susceptibility in vitro does not predict the therapeutic outcome of human Chagas disease

Therapeutic failure of benznidazole (BZ) is widely documented in Chagas disease and has been primarily associated with variations in the drug susceptibility of Trypanosoma cruzi strains. In humans, therapeutic success has been assessed by the negativation of anti-T. cruzi antibodies, a process that may take up to 10 years. A protocol for early screening of the drug resistance of infective strains would be valuable for orienting physicians towards alternative therapies, with a combination of existing drugs or new anti-T. cruzi agents. We developed a procedure that couples the isolation of parasites by haemoculture with quantification of BZ susceptibility in the resultant epimastigote forms. BZ activity was standardized with reference strains, which showed IC50 to BZ between 7.6-32 µM. The assay was then applied to isolates from seven chronic patients prior to administration of BZ therapy. The IC50 of the strains varied from 15.6 ± 3-51.4 ± 1 µM. Comparison of BZ susceptibility of the pre-treatment isolates of patients considered cured by several criteria and of non-cured patients indicates that the assay does not predict therapeutic outcome. A two-fold increase in BZ resistance in the post-treatment isolates of two patients was verified. Based on the profile of nine microsatellite loci, sub-population selection in non-cured patients was ruled out.

Search for cytotoxic agents in multiple Laurencia complex seaweed species (Ceramiales, Rhodophyta) harvested from the Atlantic Ocean with emphasis on the Brazilian State of Espírito Santo

The development of new anti-cancer drugs of algal origin represents one of the least explored frontiers in medicinal chemistry. In this regard, the diversity of micro- and macroalgae found in Brazilian coastal waters can be viewed as a largely untapped natural resource. In this report, we describe a comparative study on the cytotoxic properties of extracts obtained from the Laurencia complex: Laurencia aldingensis, L. catarinensis, L. dendroidea, L. intricata, L. translucida, L. sp, and Palisada flagellifera. All of these species were collected in the coastal waters of the State of Espírito Santo, Brazil. Four out of the twelve samples initially investigated were found to show significant levels of toxicity towards a model tumor cell line (human uterine sarcoma, MES-SA). The highest levels of cytotoxicity were typically associated with non-polar (hexane) algal extracts, while the lowest levels of cytotoxicity were found with the corresponding polar (methanol) extracts. In this report, we also describe a biological model currently in development that will not only facilitate the search for new anti-cancer drug candidates of algal origin, but also permit the identification of compounds capable of inducing the destruction of multi-drug resistant tumors with greater efficiency than the pharmaceuticals currently in clinical use.

Effect of an energy-deficient diet on populations of ciliate protozoans in bovine rumen

Ten young rumen-cannulated crossbred steers were randomly divided into two groups: a control group (C; n=4), which was fed a balanced diet for daily weight gain of 900g; and a pronounced energy-deprived group (PED; n=6), receiving 30% less of the required energy for maintenance. After 140 days of these alimentary regimes, rumen fluid and urine samples were collected for biochemical and functional tests, before feeding and at 1, 3, 6, and 9 hours after feeding. The energy-deprivation diet caused a significant reduction in the number of Entodinium, Eodinium, Isotricha, Dasytricha, Eremoplastron, Eudiplodinium, Metadinium, Charonina, Ostracodinium, and Epidinium protozoa. There was no effect of the time of sampling in both groups on the total number of ciliates in rumen fluid. A higher number of protozoan forms in binary division were recorded in the control group, at the 6th and 9th hours after feeding (P<0.019). There was a high positive correlation between the total count of protozoans in rumen fluid and glucose fermentation, ammonia, and urinary allantoin excretion index; and a negative correlation between the total count of protozoa and metilene blue reduction, and a medium correlation between the total count of protozoa and total volatile fatty acids concentration. The determination of the protozoa populations does not imply in the use of complex and hard-to-execute techniques, although it is time consuming and needs practice. This exam particularly helps in clinical expected diagnosis.

High-throughput SNP genotyping in the highly heterozygous genome of Eucalyptus: assay success, polymorphism and transferability across species

Background: High-throughput SNP genotyping has become an essential requirement for molecular breeding and population genomics studies in plant species. Large scale SNP developments have been reported for several mainstream crops. A growing interest now exists to expand the speed and resolution of genetic analysis to outbred species with highly heterozygous genomes. When nucleotide diversity is high, a refined diagnosis of the target SNP sequence context is needed to convert queried SNPs into high-quality genotypes using the Golden Gate Genotyping Technology (GGGT). This issue becomes exacerbated when attempting to transfer SNPs across species, a scarcely explored topic in plants, and likely to become significant for population genomics and inter specific breeding applications in less domesticated and less funded plant genera. Results: We have successfully developed the first set of 768 SNPs assayed by the GGGT for the highly heterozygous genome of Eucalyptus from a mixed Sanger/454 database with 1,164,695 ESTs and the preliminary 4.5X draft genome sequence for E. grandis. A systematic assessment of in silico SNP filtering requirements showed that stringent constraints on the SNP surrounding sequences have a significant impact on SNP genotyping performance and polymorphism. SNP assay success was high for the 288 SNPs selected with more rigorous in silico constraints; 93% of them provided high quality genotype calls and 71% of them were polymorphic in a diverse panel of 96 individuals of five different species. SNP reliability was high across nine Eucalyptus species belonging to three sections within subgenus Symphomyrtus and still satisfactory across species of two additional subgenera, although polymorphism declined as phylogenetic distance increased. Conclusions: This study indicates that the GGGT performs well both within and across species of Eucalyptus notwithstanding its nucleotide diversity >= 2%. The development of a much larger array of informative SNPs across multiple Eucalyptus species is feasible, although strongly dependent on having a representative and sufficiently deep collection of sequences from many individuals of each target species. A higher density SNP platform will be instrumental to undertake genome-wide phylogenetic and population genomics studies and to implement molecular breeding by Genomic Selection in Eucalyptus.

Generalized Sznajd model for opinion propagation

In the last decade the Sznajd model has been successfully employed in modeling some properties and scale features of both proportional and majority elections. We propose a version of the Sznajd model with a generalized bounded confidence rule-a rule that limits the convincing capability of agents and that is essential to allow coexistence of opinions in the stationary state. With an appropriate choice of parameters it can be reduced to previous models. We solved this model both in a mean-field approach (for an arbitrary number of opinions) and numerically in a Barabaacutesi-Albert network (for three and four opinions), studying the transient and the possible stationary states. We built the phase portrait for the special cases of three and four opinions, defining the attractors and their basins of attraction. Through this analysis, we were able to understand and explain discrepancies between mean-field and simulation results obtained in previous works for the usual Sznajd model with bounded confidence and three opinions. Both the dynamical system approach and our generalized bounded confidence rule are quite general and we think it can be useful to the understanding of other similar models.