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.

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.

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.

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.

Sudden onset of log-periodicity and superdiffusion in non-Markovian random walks with amnestically induced persistence: exact results

Random walks can undergo transitions from normal diffusion to anomalous diffusion as some relevant parameter varies, for instance the L,vy index in L,vy flights. Here we derive the Fokker-Planck equation for a two-parameter family of non-Markovian random walks with amnestically induced persistence. We investigate two distinct transitions: one order parameter quantifies log-periodicity and discrete scale invariance in the first moment of the propagator, whereas the second order parameter, known as the Hurst exponent, describes the growth of the second moment. We report numerical and analytical results for six critical exponents, which together completely characterize the properties of the transitions. We find that the critical exponents related to the diffusion-superdiffusion transition are identical in the positive feedback and negative feedback branches of the critical line, even though the former leads to classical superdiffusion whereas the latter gives rise to log-periodic superdiffusion.

On estimation and influence diagnostics for log-Birnbaum-Saunders Student-t regression models: Full Bayesian analysis

The purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regression models under right-censored survival data. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the considered model. In order to attenuate the influence of the outlying observations on the parameter estimates, we present in this paper Birnbaum-Saunders models in which a Student-t distribution is assumed to explain the cumulative damage. Also, some discussions on the model selection to compare the fitted models are given and case deletion influence diagnostics are developed for the joint posterior distribution based on the Kullback-Leibler divergence. The developed procedures are illustrated with a real data set. (C) 2010 Elsevier B.V. All rights reserved.

The log-exponentiated Weibull regression model for interval-censored data

In interval-censored survival data, the event of interest is not observed exactly but is only known to occur within some time interval. Such data appear very frequently. In this paper, we are concerned only with parametric forms, and so a location-scale regression model based on the exponentiated Weibull distribution is proposed for modeling interval-censored data. We show that the proposed log-exponentiated Weibull regression model for interval-censored data represents a parametric family of models that include other regression models that are broadly used in lifetime data analysis. Assuming the use of interval-censored data, we employ a frequentist analysis, a jackknife estimator, a parametric bootstrap and a Bayesian analysis 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. Furthermore, for different parameter settings, sample sizes and censoring percentages, various 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 straightforwardly extended to a modified deviance residual in log-exponentiated Weibull regression models for interval-censored data. (C) 2009 Elsevier B.V. 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.

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.

Deviance residuals in generalised log-gamma regression models with censored observations

In this article, we compare three residuals based on the deviance component in generalised log-gamma regression models with censored observations. 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. For all cases studied, the empirical distributions of the proposed residuals are in general symmetric around zero, but only a martingale-type residual presented negligible kurtosis for the majority of the cases studied. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for the martingale-type residual in generalised log-gamma regression models with censored data. A lifetime data set is analysed under log-gamma regression models and a model checking based on the martingale-type residual is performed.

The log-bimodal-skew-normal model. A geochemical application

The main objective of this paper is to study a logarithm extension of the bimodal skew normal model introduced by Elal-Olivero et al. [1]. The model can then be seen as an alternative to the log-normal model typically used for fitting positive data. We study some basic properties such as the distribution function and moments, and discuss maximum likelihood for parameter estimation. We report results of an application to a real data set related to nickel concentration in soil samples. Model fitting comparison with several alternative models indicates that the model proposed presents the best fit and so it can be quite useful in real applications for chemical data on substance concentration. Copyright (C) 2011 John Wiley & Sons, Ltd.

Efeitos do aparelho Jasper Jumper no tratamento da má oclusão de Classe II

OBJETIVO: o objetivo deste estudo foi avaliar os efeitos esqueléticos e dentoalveolares do tratamento de pacientes com má oclusão de Classe II com o aparelho Jasper Jumper associado ao aparelho ortodôntico fixo, comparados a um grupo controle não-tratado. MÉTODOS: a amostra foi constituída por 47 indivíduos, divididos em dois grupos: Grupo 1, contendo 25 pacientes com idade média de 12,72 anos, tratados com o aparelho Jasper Jumper por um tempo médio de 2,15 anos; Grupo 2 (controle), composto por 22 indivíduos com idade média de 12,67 anos, não-submetidos a tratamento ortodôntico e com má oclusão de Classe II, observados por um período médio de 2,12 anos. Foram avaliadas as telerradiografias ao início e ao final do tratamento ortodôntico para o Grupo 1 e do período de observação para o Grupo 2. As variáveis cefalométricas iniciais, finais e as alterações com o tratamento foram comparadas entre os grupos por meio do teste t independente. RESULTADOS: em comparação ao grupo controle, o grupo Jasper Jumper apresentou maior restrição do deslocamento anterior da maxila e maior retrusão maxilar, melhora da relação maxilomandibular, diminuição da convexidade facial, maior protrusão e intrusão dos incisivos inferiores e maior extrusão dos molares inferiores, além de maior diminuição dos trespasses horizontal e vertical e maior melhora da relação molar. CONCLUSÃO: a correção da Classe II no grupo tratado com o Jasper Jumper e aparelhagem fixa se deu principalmente devido à restrição do crescimento maxilar, protrusão e intrusão dos incisivos inferiores e extrusão dos molares inferiores.

Avaliação dos fatores determinantes da estética do perfil facial

OBJETIVO: avaliar a influência da idade, do sexo, da relação oclusal sagital, do Padrão Facial e de 8 medidas do perfil facial sobre a estética do perfil. MÉTODOS: foram utilizadas tabelas de contingência, o Teste Qui-quadrado e o coeficiente de Cramér para avaliar a possível associação entre a nota dada por 32 avaliadores (14 ortodontistas, 12 leigos e 6 artistas) para a estética do perfil de 100 brasileiros - adultos, leucodermas, portadores de selamento labial passivo - e a idade, o sexo, a relação oclusal sagital, o Padrão Facial e as variáveis da análise facial numérica do perfil. RESULTADOS: não foi observada associação entre a idade, o sexo e a relação oclusal sagital e a estética do perfil facial. A associação foi observada entre a nota recebida para a estética do perfil e o Padrão Facial, o ângulo de convexidade facial e o ângulo do terço inferior da face. CONCLUSÃO: o Padrão Facial, definido na avaliação do perfil pela convexidade do perfil facial, e a projeção anterior do mento foram, entre os fatores avaliados, os determinantes para a estética do perfil facial.

Estudo das características cefalométricas em adolescentes brasileiros portadores de Padrão Face Longa

OBJETIVO: definir valores cefalométricos esqueléticos e dentários para adolescentes brasileiros com Padrão Face Longa. MÉTODOS: a amostra foi constituída de telerradiografias em norma lateral de 30 pacientes com Face Longa, sendo 17 do sexo feminino e 13 do masculino; e 30 pacientes face Padrão I, 15 do sexo masculino e 15 do feminino, no estágio de dentadura permanente durante a adolescência. As características do Padrão Face Longa foram definidas clinicamente, pela análise facial. As seguintes grandezas cefalométricas foram avaliadas: (1) Comportamento sagital das bases apicais (SNA, SNB, ANB, NAP, Co-A, Co-Gn); (2) Comportamento vertical das bases apicais (SN.PP, SN.PM, ângulo goníaco, AFAT, AFAI, AFAM, AFP, AFATperp, AFAIperp); (3) Comportamento dentoalveolar (1-PP, 6-PP, 1-PM, 6-PM, 1.PP, IMPA); e (4) Proporção entre as alturas faciais (AFAIPerp/AFATPerp, AFAI/AFAT, AFAM/AFAI). RESULTADOS E CONCLUSÕES: o erro vertical na Face Longa concentra-se no terço inferior. A maxila apresenta uma maior altura dentoalveolar e a mandíbula, com morfologia mais vertical, mostra maior rotação no sentido horário. Essas características morfológicas e espaciais acarretam alterações sagitais e verticais no esqueleto e alterações verticais dentoalveolares. No sentido sagital, os ângulos de convexidade facial estão aumentados. No sentido vertical, as alturas faciais anteriores total e inferior estão aumentadas. O componente dentoalveolar está mais longo.