Feasible estimation of generalized linear mixed models (GLMM) with weak dependency between groups

This paper presents a two-step pseudo likelihood estimation technique for generalized linear mixed models with the random effects being correlated between groups. The core idea is to deal with the intractable integrals in the likelihood function by multivariate Taylor's approximation. The accuracy of the estimation technique is assessed in a Monte-Carlo study. An application of it with a binary response variable is presented using a real data set on credit defaults from two Swedish banks. Thanks to the use of two-step estimation technique, the proposed algorithm outperforms conventional pseudo likelihood algorithms in terms of computational time.

Genetic heterogeneity of residual variance : estimation of variance components using double hierarchical generalized linear models

Background: The sensitivity to microenvironmental changes varies among animals and may be under genetic control. It is essential to take this element into account when aiming at breeding robust farm animals. Here, linear mixed models with genetic effects in the residual variance part of the model can be used. Such models have previously been fitted using EM and MCMC algorithms. Results: We propose the use of double hierarchical generalized linear models (DHGLM), where the squared residuals are assumed to be gamma distributed and the residual variance is fitted using a generalized linear model. The algorithm iterates between two sets of mixed model equations, one on the level of observations and one on the level of variances. The method was validated using simulations and also by re-analyzing a data set on pig litter size that was previously analyzed using a Bayesian approach. The pig litter size data contained 10,060 records from 4,149 sows. The DHGLM was implemented using the ASReml software and the algorithm converged within three minutes on a Linux server. The estimates were similar to those previously obtained using Bayesian methodology, especially the variance components in the residual variance part of the model. Conclusions: We have shown that variance components in the residual variance part of a linear mixed model can be estimated using a DHGLM approach. The method enables analyses of animal models with large numbers of observations. An important future development of the DHGLM methodology is to include the genetic correlation between the random effects in the mean and residual variance parts of the model as a parameter of the DHGLM.

Likelihood prediction for generalized linear mixed models under covariate uncertainty

This paper presents the techniques of likelihood prediction for the generalized linear mixed models. Methods of likelihood prediction is explained through a series of examples; from a classical one to more complicated ones. The examples show, in simple cases, that the likelihood prediction (LP) coincides with already known best frequentist practice such as the best linear unbiased predictor. The paper outlines a way to deal with the covariate uncertainty while producing predictive inference. Using a Poisson error-in-variable generalized linear model, it has been shown that in complicated cases LP produces better results than already know methods.

Using Spatiotemporal Methods to Fill Gaps In Energy Usage Interval Data

Researchers analyzing spatiotemporal or panel data, which varies both in location and over time, often find that their data has holes or gaps. This thesis explores alternative methods for filling those gaps and also suggests a set of techniques for evaluating those gap-filling methods to determine which works best.

The Conway-Maxwell-Poisson-generalized gamma regression model with long-term survivors

In this paper, we proposed a flexible cure rate survival model by assuming the number of competing causes of the event of interest following the Conway-Maxwell distribution and the time for the event to follow the generalized gamma distribution. This distribution can be used to model survival data when the hazard rate function is increasing, decreasing, bathtub and unimodal-shaped including some distributions commonly used in lifetime analysis as particular cases. Some appropriate matrices are derived in order to evaluate local influence on the estimates of the parameters by considering different perturbations, and some global influence measurements are also investigated. Finally, data set from the medical area is analysed.

Choosing between Cox proportional hazards and logistic models for interval-censored data via bootstrap

This work develops a new methodology in order to discriminate models for interval-censored data based on bootstrap residual simulation by observing the deviance difference from one model in relation to another, according to Hinde (1992). Generally, this sort of data can generate a large number of tied observations and, in this case, survival time can be regarded as discrete. Therefore, the Cox proportional hazards model for grouped data (Prentice & Gloeckler, 1978) and the logistic model (Lawless, 1982) can befitted by means of generalized linear models. Whitehead (1989) considered censoring to be an indicative variable with a binomial distribution and fitted the Cox proportional hazards model using complementary log-log as a link function. In addition, a logistic model can be fitted using logit as a link function. The proposed methodology arises as an alternative to the score tests developed by Colosimo et al. (2000), where such models can be obtained for discrete binary data as particular cases from the Aranda-Ordaz distribution asymmetric family. These tests are thus developed with a basis on link functions to generate such a fit. The example that motivates this study was the dataset from an experiment carried out on a flax cultivar planted on four substrata susceptible to the pathogen Fusarium oxysoprum. The response variable, which is the time until blighting, was observed in intervals during 52 days. The results were compared with the model fit and the AIC values.

The canonical structure of Podolsky's generalized electrodynamics on the null-plane

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Renormalizability of generalized quantum electrodynamics

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Bayesian estimation of generalized exponential distribution under noninformative priors

The generalized exponential distribution, proposed by Gupta and Kundu (1999), is a good alternative to standard lifetime distributions as exponential, Weibull or gamma. Several authors have considered the problem of Bayesian estimation of the parameters of generalized exponential distribution, assuming independent gamma priors and other informative priors. In this paper, we consider a Bayesian analysis of the generalized exponential distribution by assuming the conventional non-informative prior distributions, as Jeffreys and reference prior, to estimate the parameters. These priors are compared with independent gamma priors for both parameters. The comparison is carried out by examining the frequentist coverage probabilities of Bayesian credible intervals. We shown that maximal data information prior implies in an improper posterior distribution for the parameters of a generalized exponential distribution. It is also shown that the choice of a parameter of interest is very important for the reference prior. The different choices lead to different reference priors in this case. Numerical inference is illustrated for the parameters by considering data set of different sizes and using MCMC (Markov Chain Monte Carlo) methods.

QTL identification for tolerance to fruit set in tomato by FAFLP markers

This study aimed to detect quantitative trait loci (QTL) by fALP (Fluorescent Amplified Fragment Length Polymorphism) markers associated to the trait tomato fruit set at high temperatures. A biparental cross between line Jab-95 (heat-tolerant) and cultivar Caribe (heat-susceptible) was made. A total of 192 plants of the F2 generation were evaluated, generating 172 polymorphic markers through six primer combinations previously identified by the Bulked Segregant Analysis technique. To construct the genetic map, 106 of the 172 markers that segregated in the expected Mendelian segregation proportion (3:1) were used. The map covered 1191.46 cM of the genome. Six trait-linked QTL were identified in the analysis of simple markers and three others by the interval-mapping methodology. These results could be highly useful in improvement programs, since heat-tolerant plants can be selected rapidly, which improves tomato fruit set.

Constrained intervals and interval spaces

Constrained intervals, intervals as a mapping from [0, 1] to polynomials of degree one (linear functions) with non-negative slopes, and arithmetic on constrained intervals generate a space that turns out to be a cancellative abelian monoid albeit with a richer set of properties than the usual (standard) space of interval arithmetic. This means that not only do we have the classical embedding as developed by H. Radström, S. Markov, and the extension of E. Kaucher but the properties of these polynomials. We study the geometry of the embedding of intervals into a quasilinear space and some of the properties of the mapping of constrained intervals into a space of polynomials. It is assumed that the reader is familiar with the basic notions of interval arithmetic and interval analysis. © 2013 Springer-Verlag Berlin Heidelberg.

Algumas distribuições de probalidade para idosos grupados e censurados

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Espaços vetoriais e topológicos de intervalos generalizados com alguns conceitos de cálculo e otimização intervalar

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Leukotoxicity of Aggregatibacter actinomycetemcomitans in generalized aggressive periodontitis in Brazilians and their family members

Objective: The purpose of this study was to examine the leukotoxin promoter types of Aggregatibacter actinomycetemcomitans clones in subjects with generalized aggressive periodontitis (GAgP) and in their family members (FM). Material and Methods: Thirty-five patients with GAgP (33.9+/-7.1 years), 33 of their FM (22.8+/-11.4 years), and 41 patients with chronic periodontitis (CP) (44.1+/-9.4 years) were clinically analyzed using the plaque index, gingival index, probing depth (PD), and clinical attachment level (CAL). Subgingival biofilm samples were collected from four interproximal periodontal sites (>PD and >CAL) of each patient. The presence of A. actinomycetemcomitans and its leukotoxic clone was confirmed by polymerase chain reaction (PCR). Results: A. actinomycetemcomitans was observed in 23 (51.1%) GAgP patients and 16 (30.1%) CP patients. Thirty-seven (94.8%) patients showed minimally leukotoxic strains and 2 (5.1%) showed highly leukotoxic strains. In the FM group, 10 (30.3%) had aggressive periodontitis (AgP), 12 (36.3%) had CP, 11 (33.3%) were periodontally healthy or had gingivitis, and 12.2% were A. actinomycetemcomitans positive. Greater full mouth PD and CAL were observed in GAgP patients positive for the bacteria than those negative for it (p<0.05), and the presence of A. actinomycetemcomitans positively correlated with GAgP (Odds ratio, 3.1; confidence interval, 1.4-7.0; p=0.009). Conclusions: The presence of A. actinomycetemcomitans was associated with the clinical condition of GAgP, with most patients exhibiting a generalized form of the disease and minimally leukotoxic clones. Most of the relatives of GAgP patients presented either CP or AgP.

Intensity and interval of recovery in strength exercise influences performance: salivary lactate and alpha amylase as biochemical markers: a pilot study

Purpose The aim of the present study was to evaluate the effects of intensity and interval of recovery on performance in the bench press exercise, and the response of salivary lactate and alpha amylase levels. Methods Ten sportsman (aged 29 ± 4 years; body mass index 26 ± 2 kg/cm2 ) were divided in two groups: G70 (performing a bench press exercise at 70 % one repetition maximum—1RM), and G90 (performing a bench press exercise at 90 %—1RM). All groups were engaged in three intervals of recovery (30, 60 and 90 s). The maximum number of repetitions (MNR) and total weight lifted were computed, and saliva samples were collected 15 min before and after different intervals of recovery. For the comparison of the performance and biochemistry parameters, ANOVA tests for repeated measurements were conducted, with a significance level set at 5 %. Results In G70, the 30 s MNR was lower than the 60 and 90 s intervals of recovery (p\0.05) and the MNR with the 60 s interval of recovery was lower than the 90 s interval of recovery (p\0.041). Similarly, in G90 with the 30 s of interval of recovery, the sets were lower than observed with the 60 and 90 s (p\0.05), and MNR with the 60 s interval of recovery was lower than the 90 s interval of recovery (p\0.05). The salivary lactate showed an increase after exercise (p\0.05) when compared with the rest period for all groups, and no effects were observed for salivary alpha amylase. Conclusions Based on this result, the sets and reps can be modified to change the recovery time. This effect is very useful to improve the performance in relationship to different fitness levels.