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.

A hands-on approach for fitting long-term survival models under the GAMLSS framework

In many data sets from clinical studies there are patients insusceptible to the occurrence of the event of interest. Survival models which ignore this fact are generally inadequate. The main goal of this paper is to describe an application of the generalized additive models for location, scale, and shape (GAMLSS) framework to the fitting of long-term survival models. in this work the number of competing causes of the event of interest follows the negative binomial distribution. In this way, some well known models found in the literature are characterized as particular cases of our proposal. The model is conveniently parameterized in terms of the cured fraction, which is then linked to covariates. We explore the use of the gamlss package in R as a powerful tool for inference in long-term survival models. The procedure is illustrated with a numerical example. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

A Bayesian Long-term Survival Model Parametrized in the Cured Fraction

The main goal of this paper is to investigate a cure rate model that comprehends some well-known proposals found in the literature. In our work the number of competing causes of the event of interest follows the negative binomial distribution. The model is conveniently reparametrized through the cured fraction, which is then linked to covariates by means of the logistic link. We explore the use of Markov chain Monte Carlo methods to develop a Bayesian analysis in the proposed model. The procedure is illustrated with a numerical example.

Power series generalized nonlinear models

We introduce in this paper a new class of discrete generalized nonlinear models to extend the binomial, Poisson and negative binomial models to cope with count data. This class of models includes some important models such as log-nonlinear models, logit, probit and negative binomial nonlinear models, generalized Poisson and generalized negative binomial regression models, among other models, which enables the fitting of a wide range of models to count data. We derive an iterative process for fitting these models by maximum likelihood and discuss inference on the parameters. The usefulness of the new class of models is illustrated with an application to a real data set. (C) 2008 Elsevier B.V. All rights reserved.

Physical disability, recent illnesses and health self-assessment in a population-based study in Sao Paulo, Brazil

Objectives. To investigate health self-assessment and to estimate the prevalence of chronic diseases and recent illnesses in people with and without physical disabilities (PD) in the state of Sao Paulo, southeastern Brazil. Study design. A Cross-sectional study comprising two population-based health surveys conducted in 2002 and 2003. Methods. A total of 8317 persons (165 with PD) were interviewed in the two studies. Variables concerning to health self-assessment; chronic disease and recent illness were compared in the people with and without PD. Negative binomial regression was used in the analysis. Results. Subjects with PD more often assessed their health as poor/very poor compared to non-disabled ones. They reported more illnesses in the 15 days prior to interview as well as more chronic diseases (skin conditions, anaemia, chronic kidney disease, stroke, depression/anxiety, migraine/headache, pulmonary diseases, hypertension, diabetes, arthritis/arthrosis/rheumatic conditions and heart disease). This higher disease prevalence can be either attributed to disability itself or be associated to gender, age and schooling. Conclusions. Subjects with PD had more recent illnesses and chronic diseases and poorer health self-assessment than non-disabled ones. Age, gender, schooling and disability have individual roles in disease development among disabled people.

Random sums of exchangeable variables and actuarial applications

In this paper we study the accumulated claim in some fixed time period, skipping the classical assumption of mutual independence between the variables involved. Two basic models are considered: Model I assumes that any pair of claims are equally correlated which means that the corresponding square-integrable sequence is exchangeable one. Model 2 states that the correlations between the adjacent claims are the same. Recurrence and explicit expressions for the joint probability generating function are derived and the impact of the dependence parameter (correlation coefficient) in both models is examined. The Markov binomial distribution is obtained as a particular case under assumptions of Model 2. (C) 2007 Elsevier B.V. All rights reserved.

Prevalence and nonrandom distribution of exonic mutations in interferon regulatory factor 6 in 307 families with Van der Woude syndrome and 37 families with popliteal pterygium syndrome

Purpose: Interferon regulatory factor 6 encodes a member of the IRF family of transcription factors. Mutations in interferon regulatory factor 6 cause Van der Woude and popliteal pterygium syndrome, two related orofacial clefting disorders. Here, we compared and contrasted the frequency and distribution of exonic Mutations in interferon regulatory factor 6 between two large geographically distinct collections of families with Van der Woude and between one collection of families with popliteal pterygium syndrome. Methods: We performed direct sequence analysis of interferon regulatory factor 6 exons oil samples from three collections, two with Van der Woude and one with popliteal pterygium syndrome. Results: We identified mutations in interferon regulatory factor 6 exons in 68% of families in both Van der Woude collections and in 97% of families with popliteal pterygium syndrome. In sum, 106 novel disease-causing variants were found. The distribution of mutations in the interferon regulatory factor 6 exons in each collection was not random; exons 3, 4, 7, and 9 accounted for 80%. In the Van der Woude collections, the mutations were evenly divided between protein truncation and missense, whereas most mutations identified in the popliteal pterygium syndrome collection were missense. Further, the missense mutations associated with popliteal pterygium syndrome were localized significantly to exon 4, at residues that are predicted to bind directly to DNA. Conclusion: The nonrandom distribution of mutations in the interferon regulatory factor 6 exons suggests a two-tier approach for efficient mutation screens for interferon regulatory factor 6. The type and distribution of mutations are consistent with the hypothesis that Van der Woude is caused by haploinsufficiency of interferon regulatory factor 6. Oil the other hand, the distribution of popliteal pterygium syndrome-associated mutations suggests a different, though not mutually exclusive, effect oil interferon regulatory factor 6 function. Genet Med 2009:11(4):241-247.

A New Class of Non Negative Distributions Generated by Symmetric Distributions

In this article, we study a new class of non negative distributions generated by the symmetric distributions around zero. For the special case of the distribution generated using the normal distribution, properties like moments generating function, stochastic representation, reliability connections, and inference aspects using methods of moments and maximum likelihood are studied. Moreover, a real data set is analyzed, illustrating the fact that good fits can result.

Beta-binomial/Poisson regression models for repeated bivariate counts

We analyze data obtained from a study designed to evaluate training effects on the performance of certain motor activities of Parkinson`s disease patients. Maximum likelihood methods were used to fit beta-binomial/Poisson regression models tailored to evaluate the effects of training on the numbers of attempted and successful specified manual movements in 1 min periods, controlling for disease stage and use of the preferred hand. We extend models previously considered by other authors in univariate settings to account for the repeated measures nature of the data. The results suggest that the expected number of attempts and successes increase with training, except for patients with advanced stages of the disease using the non-preferred hand. Copyright (c) 2008 John Wiley & Sons, Ltd.