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.

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.

Different Approaches for Modeling Grouped Survival Data: A Mango Tree Study

Interval-censored survival data, in which the event of interest is not observed exactly but is only known to occur within some time interval, occur very frequently. In some situations, event times might be censored into different, possibly overlapping intervals of variable widths; however, in other situations, information is available for all units at the same observed visit time. In the latter cases, interval-censored data are termed grouped survival data. Here we present alternative approaches for analyzing interval-censored data. We illustrate these techniques using a survival data set involving mango tree lifetimes. This study is an example of grouped survival data.

A generalized modified Weibull distribution for lifetime modeling

A four parameter generalization of the Weibull distribution capable of modeling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone as well as non-monotone failure rates, which are quite common in lifetime problems and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the Weibull, extreme value, exponentiated Weibull, generalized Rayleigh and modified Weibull distributions, among others. We derive two infinite sum representations for its moments. The density of the order statistics is obtained. The method of maximum likelihood is used for estimating the model parameters. Also, the observed information matrix is obtained. Two applications are presented to illustrate the proposed distribution. (C) 2008 Elsevier B.V. All rights reserved.

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.

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.

On estimation and influence diagnostics for zero-inflated negative binomial regression models

The zero-inflated negative binomial model is used to account for overdispersion detected in data that are initially analyzed under the zero-Inflated Poisson model A frequentist analysis a jackknife estimator and a non-parametric bootstrap for parameter estimation of zero-inflated negative binomial regression models are considered In addition an EM-type algorithm is developed for performing maximum likelihood estimation Then the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and some ways to perform global influence analysis are derived In order to study departures from the error assumption as well as the presence of outliers residual analysis based on the standardized Pearson residuals is discussed The relevance of the approach is illustrated with a real data set where It is shown that zero-inflated negative binomial regression models seems to fit the data better than the Poisson counterpart (C) 2010 Elsevier B V All rights reserved

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

General results for the beta-modified Weibull distribution

We study in detail the so-called beta-modified Weibull distribution, motivated by the wide use of the Weibull distribution in practice, and also for the fact that the generalization provides a continuous crossover towards cases with different shapes. The new distribution is important since it contains as special sub-models some widely-known distributions, such as the generalized modified Weibull, beta Weibull, exponentiated Weibull, beta exponential, modified Weibull and Weibull distributions, among several others. It also provides more flexibility to analyse complex real data. Various mathematical properties of this distribution are derived, including its moments and moment generating function. We examine the asymptotic distributions of the extreme values. Explicit expressions are also derived for the chf, mean deviations, Bonferroni and Lorenz curves, reliability and entropies. The estimation of parameters is approached by two methods: moments and maximum likelihood. We compare by simulation the performances of the estimates from these methods. We obtain the expected information matrix. Two applications are presented to illustrate the proposed distribution.

The exponentiated generalized gamma distribution with application to lifetime data

A four-parameter extension of the generalized gamma distribution capable of modelling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone and non-monotone failure rate functions, which are quite common in lifetime data analysis and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the exponentiated Weibull, exponentiated generalized half-normal, exponentiated gamma and generalized Rayleigh, among others. We derive two infinite sum representations for its moments. We calculate the density of the order statistics and two expansions for their moments. The method of maximum likelihood is used for estimating the model parameters and the observed information matrix is obtained. Finally, a real data set from the medical area is analysed.

An integrated molecular map of yellow passion fruit based on simultaneous maximum-likelihood estimation of linkage and linkage phases

The development of genetic maps for auto-incompatible species, such as the yellow passion fruit (Passiflora edulis Sims f.flavicarpa Deg.) is restricted due to the unfeasibility of obtaining traditional mapping populations based on inbred lines. For this reason, yellow passion fruit linkage maps were generally constructed using a strategy known as two-way pseudo-testeross, based on monoparental dominant markers segregating in a 1:1 fashion. Due to the lack of information from these markers in one of the parents, two individual (parental) maps were obtained. However, integration of these maps is essential, and biparental markers can be used for such an operation. The objective of our study was to construct an integrated molecular map for a full-sib population of yellow passion fruit combining different loci configuration generated from amplified fragment length polymorphisms (AFLPs) and microsatellite markers and using a novel approach based on simultaneous maximum-likelihood estimation of linkage and linkage phases, specially designed for outcrossing species. Of the total number of loci, approximate to 76%, 21%, 0.7%, and 2.3% did segregate in 1:1, 3:1, 1:2:1, and 1:1:1:1 ratios, respectively. Ten linkage groups (LGs) were established with a logarithm of the odds (LOD) score >= 5.0 assuming a recombination fraction : <= 0.35. On average, 24 markers were assigned per LG, representing a total map length of 1687 cM, with a marker density of 6.9 cM. No markers were placed as accessories on the map as was done with previously constructed individual maps.

Growth and haematology of pacu, Piaractus mesopotamicus, fed diets with varying protein to energy ratio

Haematopoiesis and blood cells` functions can be influenced by dietary concentration of nutrients. This paper studied the effects of dietary protein:energy ratio on the growth and haematology of pacu, Piaractus mesopotamicus. Fingerling pacu (15.5 +/- 0.4 g) were fed twice a day for 10 weeks until apparent saciety with diets containing 220, 260, 300, 340 or 380 g kg(-1) crude protein (CP) and 10.88, 11.72, 12.55, 13.39, 14.22 MJ kg(-1) digestible energy (DE) in a totally randomized experimental design, 5 x 5 factorial scheme (n=3). Weight gain and specific growth rate were affected (P < 0.05) by protein level only. Protein efficiency ratio decreased (P < 0.05) with increasing dietary protein at all levels of dietary energy. Daily feed intake decreased (P < 0.05) with increasing dietary energy. Mean corpuscular haemoglobin concentration was affected (P < 0.05) by DE and interaction between dietary CP and DE. Total plasma protein increased (P < 0.05) with dietary protein and energy levels. Plasma glucose decreased (P < 0.05) with increasing dietary protein. The CP requirement and optimum protein:energy ratio for weight gain of pacu fingerlings, determined using broken-line model, were 271 g kg(-1) and 22.18 g CP MJ(-1) DE respectively. All dietary CP and DE levels studied did not pose damages to fish health.

Calcium: magnesium ratio in amendments of soil acidity: nutrition and initial development of corn plants in a Humic Alic Cambisol

The variation in the Ca:Mg ratio in amendments used to neutralize soil acidity is one way of altering the availability of those nutrients to the plants in acid soils. The objective of the work was to evaluate the effect of different proportions of calcium and magnesium in the form of CaCO(3) and MgCO(3) Oil the nutrient uptake, and initial production of dry matter by corn plants. The study was carried out in greenhouse conditions, in Lages, SC, with a completely randomized experimental design, with three replications. The treatments were the application of equivalent to 21.0 t ha(-1) of lime, using mixtures of CaCO(3) and MgCO(3) in several proportions to obtain different Ca:Mg ratios (1: 1, 2:1, 4:1, 8:1, 16:1 and 32:1), on a Humic Alic Cambisol, with 310 g kg(-1) of clay. The application of treatments caused the following Ca:Mg ratios in the CEC: 1. 1: 1, 2.1:1, 4.0:1, 8.1:1, 16.4:1 and 31.8:1. The high concentrations of exchangeable Ca in soil caused by addition of lime with high Ca content inhibited the uptake of Mg and K by the corn plants. The increase in the soil Ca:Mg ratio reduced the dry matter production and height of plants in the initial stage of development.

Hand position on the bunch and source-sink ratio influence the banana fruit susceptibility to crown rot disease

The postharvest development of crown rot of bananas depends notably on the fruit susceptibility to this disease at harvest. It has been shown that fruit susceptibility to crown rot is variable and it was suggested that this depends on environmental preharvest factors. However, little is known about the preharvest factors influencing this susceptibility. The aim of this work was to evaluate the extent to which fruit filling characteristics during growth and the fruit development stage influence the banana susceptibility to crown rot. This involved evaluating the influence of (a) the fruit position at different levels of the banana bunch (hands) and (b) changing the source-sink ratio (So-Si ratio), on the fruit susceptibility to crown rot. The fruit susceptibility was determined by measuring the internal necrotic surface (INS) after artificial inoculation of Colletotrichum musae. A linear correlation (r = -0.95) was found between the hand position on the bunch and the INS. The So-Si ratio was found to influence the pomological characteristics of the fruits and their susceptibility to crown rot. Fruits of bunches from which six hands were removed (two hands remaining on the bunch) proved to be significantly less susceptible to crown rot (INS = 138.3 mm 2) than those from bunches with eight hands (INS = 237.9 mm 2). The banana susceptibility to crown rot is thus likely to be influenced by the fruit development stage and filling characteristics. The present results highlight the importance of standardising hand sampling on a bunch when testing fruit susceptibility to crown rot. They also show that hand removal in the field has advantages in the context of integrated pest management, making it possible to reduce fruit susceptibility to crown rot while increasing fruit size.

Assessment of how pregnancy modifies plasma lead and plasma/whole blood lead ratio in ALAD 1-1 genotype women

Pregnant women are one of the most sensitive populations to the toxic effects associated with lead (Pb) exposure. These effects are primarily associated with plasma Pb (Pb-P), which reflects the most rapidly exchangeable fraction of Pb in the bloodstream, and elevated maternal Pb-P may be more relevant to foetal Pb exposure than whole blood Pb (Pb-B). We investigated how pregnancy affects Pb-B, Pb-P and %Pb-P/Pb-B ratios without the influence of the 6-aminolevulinic acid dehydratase (ALAD) G177C polymorphism, which is a major genetic factor influencing Pb-B, Pb-P and %Pb-P/Pb-B ratios. Genotypes for the ALAD G177C polymorphism were determined by PCR and restriction fragment length digestion in nine pregnant and 20 non-pregnant women, aged 18-33, environmentally exposed to Pb. Here, we included only women with ALAD 1-1 genotype. Pb-P and Pb-B were determined by inductively coupled plasma mass spectrometry and by graphite furnace atomic absorption spectrometry, respectively. We found no differences in Pb-B (P > 0.05). However, pregnant women had a 2-fold increase in Pb-P and a 3-fold increase in %Pb-P/Pb-B (both P < 0.01) compared to nonpregnant women. These alterations in Pb concentrations associated with pregnancy are similar to those associated with different ALAD gene variants. We can now better appreciate how pregnancy affects foetal exposure to Pb without the influence of this important genetic factor.