Influence diagnostics for polyhazard models in the presence of covariates

In this paper, we present various diagnostic methods for polyhazard models. Polyhazard models are a flexible family for fitting lifetime data. Their main advantage over the single hazard models, such as the Weibull and the log-logistic models, is to include a large amount of nonmonotone hazard shapes, as bathtub and multimodal curves. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. A discussion of the computation of the likelihood displacement as well as the normal curvature in the local influence method are presented. Finally, an example with real data is given for illustration.

Residuals for log-Burr XII regression models in survival analysis

In this paper, we compare three residuals to assess departures from the error assumptions as well as to detect outlying observations in log-Burr XII regression models with censored observations. These residuals can also be used for the log-logistic regression model, which is a special case of the log-Burr XII regression model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and the empirical distribution of each residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to the modified martingale-type residual in log-Burr XII regression models with censored data.

Log-Burr XII regression models with censored data

In survival analysis applications, the failure rate function may frequently present a unimodal shape. In such case, the log-normal or log-logistic distributions are used. In this paper, we shall be concerned only with parametric forms, so a location-scale regression model based on the Burr XII distribution is proposed for modeling data with a unimodal failure rate function as an alternative to the log-logistic regression model. Assuming censored data, we consider a classic analysis, a Bayesian analysis and a jackknife estimator for the parameters of the proposed model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the log-logistic and log-Burr XII regression models. Besides, we use sensitivity analysis to detect influential or outlying observations, and residual analysis is used to check the assumptions in the model. Finally, we analyze a real data set under log-Buff XII regression models. (C) 2008 Published by Elsevier B.V.

Predicting the columnar-to-equiaxed transition for a distribution of nucleation undercoolings

A deterministic mathematical model for steady-state unidirectional solidification is proposed to predict the columnar-to-equiaxed transition. In the model, which is an extension to the classic model proposed by Hunt [Hunt JD. Mater Sci Eng 1984;65:75], equiaxed grains nucleate according to either a normal or a log-normal distribution of nucleation undercoolings. Growth maps are constructed, indicating either columnar or equiaxed solidification as a function of the velocity of isotherms and temperature gradient. The fields A columnar and equiaxed growth change significantly with the spread of the nucleation undercooling distribution. Increasing the spread Favors columnar solidification if the dimensionless velocity of the isotherms is larger than 1. For a velocity less than 1, however, equiaxed solidification is initially favored, but columnar solidification is enhanced for a larger increase in the spread. This behavior was confirmed by a stochastic model, which showed that an increase in the distribution spread Could change the grain structure from completely columnar to 50% columnar grains. (c) 2008 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Generalized log-gamma regression models with cure fraction

In this paper, the generalized log-gamma regression model is modified to allow the possibility that long-term survivors may be present in the data. This modification leads to a generalized log-gamma regression model with a cure rate, encompassing, as special cases, the log-exponential, log-Weibull and log-normal regression models with a cure rate typically used to model such data. The models attempt to simultaneously estimate the effects of explanatory variables on the timing acceleration/deceleration of a given event and the surviving fraction, that is, the proportion of the population for which the event never occurs. The normal curvatures of local influence are derived under some usual perturbation schemes and two martingale-type residuals are proposed to assess departures from the generalized log-gamma error assumption as well as to detect outlying observations. Finally, a data set from the medical area is analyzed.

The generalized log-gamma mixture model with covariates: local influence and residual analysis

In a sample of censored survival times, the presence of an immune proportion of individuals who are not subject to death, failure or relapse, may be indicated by a relatively high number of individuals with large censored survival times. In this paper the generalized log-gamma model is modified for the possibility that long-term survivors may be present in the data. The model attempts to separately estimate the effects of covariates on the surviving fraction, that is, the proportion of the population for which the event never occurs. The logistic function is used for the regression model of the surviving fraction. Inference for the model parameters is considered via maximum likelihood. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. Finally, a data set from the medical area is analyzed under the log-gamma generalized mixture model. A residual analysis is performed in order to select an appropriate model.

A Log-Linear Regression Model for the Beta-Weibull Distribution

We introduce the log-beta Weibull regression model based on the beta Weibull distribution (Famoye et al., 2005; Lee et al., 2007). We derive expansions for the moment generating function which do not depend on complicated functions. The new regression model represents a parametric family of models that includes as sub-models several widely known regression models that can be applied to censored survival data. We employ a frequentist analysis, a jackknife estimator, and a parametric bootstrap for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Further, for different parameter settings, sample sizes, and censoring percentages, several simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We define martingale and deviance residuals to evaluate the model assumptions. The extended regression model is very useful for the analysis of real data and could give more realistic fits than other special regression models.

Poly(aniline)/poly(methylmethacrylate) films obtained from waterborne latex nanoparticles

This paper presents the characterization of poly(aniline) (PANI) and poly(methyl methacrylate) (PMMA) coatings obtained by mixing PANI with PMMA aqueous dispersions (latex particles). These dispersions were characterized by using dynamic light scattering for sizing, zeta-potential analysis and thermal analysis. PMMA and PANI/PMMA dispersions show negative charged particles with zeta potential greater than |40| mV, a zeta-average diameter of 64 nm for pure PMMA and a bi-modal particle-size distribution centered at 45 and 120 nm for a mixture with 25% w/w of PANI. Films obtained by casting were characterized by using scanning electron microscopy and they show a conductivity increase upon PANI content reaching a value of 1 mS cm(-1) for a film with 25% w/w of PANI. In addition, Raman spectroscopy have shown the presence of the conducting form of PANI in the films and cyclic voltammetry experiments corroborated that they are electroactive in both acid and neutral solutions.

Influence of Granulometry and Organic Treatment of a Brazilian Montmorillonite on the Properties of Poly(styrene-co-n-butyl acrylate)/Layered Silicate Nanocomposites Prepared by Miniemulsion Polymerization

The influence of granulometry and organic treatment of a Brazilian montmorillonite (MMT) clay on the synthesis and properties of poly(styrene-co-n-butyl acrylate)/layered silicate nanocomposites was studied. Hybrid latexes of poly(styrene-co-butyl acrylate)/MMT were synthesized via miniemulsion polymerization using either sodium or organically modified MMT. Five clay granulometries ranging from clay particles smaller than 75 mu m to colloidal size were selected. The size of the clay particles was evaluated by Specific surface area measurements (BET). Cetyl trimethyl ammonium chloride was used as an organic modifier to enhance the clay compatibility with the monomer phase before polymerization and to improve the clav distribution and dispersion within the polymeric matrix after polymerization. The sodium and organically modified natural clays as well as the composites were characterized by X-ray diffraction analysis. The latexes were characterized by dynamic light scattering. The mechanical, thermal, and rheological properties of the composites obtained were characterized by dynamical-mechanical analysis, thermogravimetry, and small amplitude oscillatory, shear tests, respectively. The results showed that smaller the size of the organically modified MMT, the higher the degree of exfoliation of nanoplatelets. Hybrid latexes in presence of Na-MMT resulted in materials with intercalated structures. (C) 2009 Wiley, Periodicals, Inc. J Appl Polym Sci 112: 1949-1958, 2009

The generalized inverse Weibull distribution

The inverse Weibull distribution has the ability to model failure rates which are quite common in reliability and biological studies. A three-parameter generalized inverse Weibull distribution with decreasing and unimodal failure rate is introduced and studied. We provide a comprehensive treatment of the mathematical properties of the new distribution including expressions for the moment generating function and the rth generalized moment. The mixture model of two generalized inverse Weibull distributions is investigated. The identifiability property of the mixture model is demonstrated. For the first time, we propose a location-scale regression model based on the log-generalized inverse Weibull distribution for modeling lifetime data. In addition, we develop some diagnostic tools for sensitivity analysis. Two applications of real data are given to illustrate the potentiality of the proposed regression model.

A log-extended Weibull regression model

A bathtub-shaped failure rate function is very useful in survival analysis and reliability studies. The well-known lifetime distributions do not have this property. For the first time, we propose a location-scale regression model based on the logarithm of an extended Weibull distribution which has the ability to deal with bathtub-shaped failure rate functions. We use the method of maximum likelihood to estimate the model parameters and some inferential procedures are presented. We reanalyze a real data set under the new model and the log-modified Weibull regression model. We perform a model check based on martingale-type residuals and generated envelopes and the statistics AIC and BIC to select appropriate models. (C) 2009 Elsevier B.V. All rights reserved.

Log-modified Weibull regression models with censored data: Sensitivity and residual analysis

This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

Temporal and spatial distribution of anurans in the Pampa Region (Santa Maria, RS).

The present study aimed to determine the richness, occurrence constancy, reproductive modes. standard of abundance distribution, season of vocalization and to test correlation among climatic variables and activity of vocalization of anurans in a region of the Pampa Biome, Santa Maria, Rio Grande do Sul State. During the period of Novernber/2001 to October/2002 monthly collections were carried out utilizing the `survey at breeding site` method and examination of specimens kept in the Colecao Herpetologica do Setor de Zoologia da Universidade Federal de Santa Maria (ZUFSM). Tire Occurrence of 25 species of anurans was recorded. The anurofauna recorded represents 30% of the species known to Occur in Rio Grande do Sul, and comprises species generally associated with grasslands in this state and neighboring countries. Four reproductive modes were recorded: mode 1 (14 species: 58.3%) mode 11 and 30 (9 species` 37.5%) and mode 24 (1 species; 4.2%). The low diversification of reproductive modes is likely related to the homogeneity of the grassland habitat. Most species were constant or accessory in the Study area and the species abundance distribution patterns fit in the Broken Stick and Log-normal models. characterized by homogeneity of species abundance distribution. Most species showed great plasticity in habitat. but few were plastic in vocalization sites use. There was a weak positive correlation between species richness and precipitation. There was also a weak positive correlation between the abundance of species calling activity and maximum average temperatures. These correlations indicated that, in the study area. the abundance of calling males is more affected by the temperature, and species richness is more affected by precipitation, despite the fact that significantly higher species richness occurs during the hottest period of the year. These results showed that the climatological variables examined were not enough to explain the seasonal occurrence of species, thus the influence of other environmental variables merit to be tested in future studies.

Distribution of HDL-cholesterol and non-HDL-cholesterol in Brazilian children and adolescents - The Floripa study

Background and aims: HDL-cholesterol (HDL-C) and non-HDL-cholesterol (nHDL-C) are involved in atherosclerosis. The aim of this study was to determine the distribution of HDL-C and nHDL-C and its association with cardiovascular and socio-cultural variables in a pediatric Brazilian sample. Methods and results: Children and adolescents from Florianopolis were randomly selected and a structured questionnaire was administered, a physical examination was performed and a blood sample was collected. Enzymatic and Direct methods in vitro were used to determine the total cholesterol and HDL-cholesterol levels. The associations among HDL-C and nHDL-C and the described variables were tested by odds ratio and logistic regression. A total of 1009 individuals were examined. Based on the Brazilian criteria, 23% were classified with low levels of HDL-C and 25% with high levels of non-HDL-C. After multivariate analysis there were significant associations among low HDL-C and high C-reactive protein (OR, 3.3; 95% CI, 2.1-5.2), paternal tobacco use (OR, 1.5; 95% CI, 1.1-2.1), and high triceps-to-subscapular index (OR, 1.5; 95% CI, 1.1-2.2). There were also significant associations among high nHDL-C and high waist circumference (OR, 1.95; 95% CI, 1.16-3.29), black skin color (OR, 1.78; 95% CI, 1.06-3.06), and high income (OR, 1.48; 95% CI, 1.09-2.02). Conclusions: In this sample, low levels of HDL-C were associated with other clinical variables such as a centripetal fat pattern and C-reactive protein, and n-HDL-C was associated with abdominal obesity, skin color and economic class. (C) 2009 Elsevier B. V. All rights reserved.

Prevalence and distribution of the GBV-C/HGV among HIV-1-infected patients under anti-retroviral therapy

Infection with GB virus C (GBV-C) or hepatitis G virus (HGV) is highly prevalent among HIV/AIDS patients. GBV-C/HGV viremia has not been associated with liver disease and seems to slow HIV disease progression. To study the GBV-C/HGV genotypes prevalence among HIV/AIDS patients and its association with HIV viral load (VL) and CD4+ lymphocyte counts. From February 2003 to February 2004, we analyzed 210 HIV-1-infected subjects who were on anti-retroviral therapy (ART). For 63 of them a PCR-nested to the non-coding 5` (5`NCR) region of the GBV-C/HGV was done, and for 49 a DNA direct sequencing was done. A phylogenetic analysis was performed by PHYLIP program. 63(30%) of the HIV-1-infected patients were co-infected with GBV-C/HGV. The phylogenetic analysis revealed the following genotypes (and respective relative frequencies): 1(10%), 2a (41%), 2b (43%), and 3 (6%). Co-infected patients presented lower HIV-1 VL and higher T CD4+ lymphocyte cells counts as compared with patients negative for GBV-C/HGV sequences (log = 4.52 vs. 4.71, p = 0.036), and T CD4+ lymphocyte counts (cells/mm(3) = 322.6 vs. 273.5, p = 0.081, respectively). T CD4+ cells counts equal to, or higher than, 200/mm(3) were significantly more common among co-infected patients than among HIV-infected-only patients (p = 0.042). The lowest T CD4+ cells counts were associated with genotype 1 and the highest with genotype 2b (p = 0.05). The GBV-C/HGV infection prevalence was 30% among HIV-1-infected subjects, and was associated with lower VL and higher CD4+ lymphocyte counts. GBV-C/HGV genotype 2b may be associated with better immunological response. Published by Elsevier B.V.