The Poisson-exponential regression model under different latent activation schemes

In this paper, a new family of survival distributions is presented. It is derived by considering that the latent number of failure causes follows a Poisson distribution and the time for these causes to be activated follows an exponential distribution. Three different activation schemes are also considered. Moreover, we propose the inclusion of covariates in the model formulation in order to study their effect on the expected value of the number of causes and on the failure rate function. Inferential procedure based on the maximum likelihood method is discussed and evaluated via simulation. The developed methodology is illustrated on a real data set on ovarian cancer.

A Poisson mixed model with nonnormal random effect distribution

In this paper, we propose a random intercept Poisson model in which the random effect is assumed to follow a generalized log-gamma (GLG) distribution. This random effect accommodates (or captures) the overdispersion in the counts and induces within-cluster correlation. We derive the first two moments for the marginal distribution as well as the intraclass correlation. Even though numerical integration methods are, in general, required for deriving the marginal models, we obtain the multivariate negative binomial model from a particular parameter setting of the hierarchical model. An iterative process is derived for obtaining the maximum likelihood estimates for the parameters in the multivariate negative binomial model. Residual analysis is proposed and two applications with real data are given for illustration. (C) 2011 Elsevier B.V. All rights reserved.

The role of clouds in improving the regression model for hourly values of diffuse solar radiation

The study introduces a new regression model developed to estimate the hourly values of diffuse solar radiation at the surface. The model is based on the clearness index and diffuse fraction relationship, and includes the effects of cloud (cloudiness and cloud type), traditional meteorological variables (air temperature, relative humidity and atmospheric pressure observed at the surface) and air pollution (concentration of particulate matter observed at the surface). The new model is capable of predicting hourly values of diffuse solar radiation better than the previously developed ones (R-2 = 0.93 and RMSE = 0.085). A simple version with a large applicability is proposed that takes into consideration cloud effects only (cloudiness and cloud height) and shows a R-2 = 0.92. (C) 2011 Elsevier Ltd. All rights reserved.

The geometric Birnbaum-Saunders regression model with cure rate

In this paper, we propose a cure rate survival model by assuming the number of competing causes of the event of interest follows the Geometric distribution and the time to event follow a Birnbaum Saunders distribution. We consider a frequentist analysis for parameter estimation of a Geometric Birnbaum Saunders model with cure rate. Finally, to analyze a data set from the medical area. (C) 2011 Elsevier B.V. All rights reserved.

THE LOG-BURR XII REGRESSION MODEL FOR GROUPED SURVIVAL DATA

The log-Burr XII regression model for grouped survival data is evaluated in the presence of many ties. The methodology for grouped survival data is based on life tables, where the times are grouped in k intervals, and we fit discrete lifetime regression models to the data. The model parameters are estimated by maximum likelihood and jackknife methods. To detect influential observations in the proposed model, diagnostic measures based on case deletion, so-called 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 these measures, the total local influence and influential estimates are also used. We conduct Monte Carlo simulation studies to assess the finite sample behavior of the maximum likelihood estimators of the proposed model for grouped survival. A real data set is analyzed using a regression model for grouped data.

A log-Birnbaum-Saunders regression model with asymmetric errors

This paper introduces a skewed log-Birnbaum-Saunders regression model based on the skewed sinh-normal distribution proposed by Leiva et al. [A skewed sinh-normal distribution and its properties and application to air pollution, Comm. Statist. Theory Methods 39 (2010), pp. 426-443]. Some influence methods, such as the local influence and generalized leverage, are presented. Additionally, we derived the normal curvatures of local influence under some perturbation schemes. An empirical application to a real data set is presented in order to illustrate the usefulness of the proposed model.

The log-exponentiated generalized gamma regression model for censored data

For the first time, we introduce a generalized form of the exponentiated generalized gamma distribution [Cordeiro et al. The exponentiated generalized gamma distribution with application to lifetime data, J. Statist. Comput. Simul. 81 (2011), pp. 827-842.] that is the baseline for the log-exponentiated generalized gamma regression model. The new distribution can accommodate increasing, decreasing, bathtub- and unimodal-shaped hazard functions. A second advantage is that it includes classical distributions reported in the lifetime literature as special cases. We obtain explicit expressions for the moments of the baseline distribution of the new regression model. The proposed model can be applied to censored data since it includes as sub-models several widely known regression models. It therefore can be used more effectively in the analysis of survival data. We obtain maximum likelihood estimates for the model parameters by considering censored data. We show that our extended regression model is very useful by means of two applications to real data.

The negative binomial-beta Weibull regression model to predict the cure of prostate cancer

In this article, for the first time, we propose the negative binomial-beta Weibull (BW) regression model for studying the recurrence of prostate cancer and to predict the cure fraction for patients with clinically localized prostate cancer treated by open radical prostatectomy. The cure model considers that a fraction of the survivors are cured of the disease. The survival function for the population of patients can be modeled by a cure parametric model using the BW distribution. We derive an explicit expansion for the moments of the recurrence time distribution for the uncured individuals. The proposed distribution can be used to model survival data when the hazard rate function is increasing, decreasing, unimodal and bathtub shaped. Another advantage is that the proposed model includes as special sub-models some of the well-known cure rate models discussed in the literature. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes. We analyze a real data set for localized prostate cancer patients after open radical prostatectomy.

A log-linear regression model for the beta-Birnbaum-Saunders distribution with censored data

The beta-Birnbaum-Saunders (Cordeiro and Lemonte, 2011) and Birnbaum-Saunders (Birnbaum and Saunders, 1969a) distributions have been used quite effectively to model failure times for materials subject to fatigue and lifetime data. We define the log-beta-Birnbaum-Saunders distribution by the logarithm of the beta-Birnbaum-Saunders distribution. Explicit expressions for its generating function and moments are derived. We propose a new log-beta-Birnbaum-Saunders regression model that can be applied to censored data and be used more effectively in survival analysis. We obtain the maximum likelihood estimates of the model parameters for censored data and investigate influence diagnostics. The new location-scale regression model is modified for the possibility that long-term survivors may be presented in the data. Its usefulness is illustrated by means of two real data sets. (C) 2011 Elsevier B.V. All rights reserved.

Men's health: a population-based study on social inequalities

This study evaluates social inequalities in health according to level of schooling in the male population. This was a cross-sectional, population-based study with a sample of 449 men ranging from 20 to 59 years of age and living in Campinas, Sao Paulo State, Brazil. The chi-square test was used to verify associations, and a Poisson regression model was used to estimate crude and adjusted prevalence ratios. Men with less schooling showed higher rates of alcohol consumption and dependence, smoking, sedentary lifestyle during leisure time, and less healthy eating habits, in addition to higher prevalence of bad or very bad self-rated health, at least one chronic disease, hypertension, and other health problems. No differences were detected between the two schooling strata in terms of use of health services, except for dental services. The findings point to social inequality in health-related behaviors and in some health status indicators. However, possible equity was observed in the use of nearly all types of health services.

Association between particulate matter air pollution and monthly inhalation and nebulization procedures in Ribeirao Preto, Sao Paulo State, Brazil

The study was designed to investigate the impact of air pollution on monthly inhalation/nebulization procedures in Ribeirao Preto, Sao Paulo State, Brazil, from 2004 to 2010. To assess the relationship between the procedures and particulate matter (PM10) a Bayesian Poisson regression model was used, including a random factor that captured extra-Poisson variability between counts. Particulate matter was associated with the monthly number of inhalation/nebulization procedures, but the inclusion of covariates (temperature, precipitation, and season of the year) suggests a possible confounding effect. Although other studies have linked particulate matter to an increasing number of visits due to respiratory morbidity, the results of this study suggest that such associations should be interpreted with caution.

Are mental health problems and depression associated with bruxism in children?

Renner AC, da Silva AAM, Rodriguez JDM, Simoes VMF, Barbieri MA, Bettiol H, Thomaz EBAF, Saraiva MC. Are mental health problems and depression associated with bruxism in children? Community Dent Oral Epidemiol 2011. (C) 2011 John Wiley & Sons A/S Abstract Objectives: Previous studies have found an association between bruxism and emotional and behavioral problems in children, but reported data are inconsistent. The objective of this study was to estimate the prevalence of bruxism, and of its components clenching and grinding, and its associations with mental problems and depression. Methods: Data from two Brazilian birth cohorts were analyzed: one from 869 children in Ribeirao Preto RP (Sao Paulo), a more developed city, and the other from 805 children in Sao Luis SL (Maranhao). Current bruxism evaluated by means of a questionnaire applied to the parents/persons responsible for the children was defined when the habit of tooth clenching during daytime and/or tooth grinding at night still persisted until the time of the assessment. Additionally, the lifetime prevalence of clenching during daytime only and grinding at night only was also evaluated. Mental health problems were investigated using the Strength and Difficulties Questionnaire (SDQ) and depression using the Childrens Depression Inventory (CDI). Analyses were carried out for each city: with the SDQ subscales (emotional symptoms, conduct problems, peer problems, attention/hyperactivity disorder), with the total score (sum of the subscales), and with the CDI. These analyses were performed considering different response variables: bruxism, clenching only, and grinding only. The risks were estimated using a Poisson regression model. Statistical inferences were based on 95% confidence intervals (95% CI). Results: There was a high prevalence of current bruxism: 28.7% in RP and 30.0% in SL. The prevalence of clenching was 20.3% in RP and 18.8% in SL, and grinding was found in 35.7% of the children in RP and 39.1% in SL. Multivariable analysis showed a significant association of bruxism with emotional symptoms and total SDQ score in both cities. When analyzed separately, teeth clenching was associated with emotional symptoms, peer problems, and total SDQ score; grinding was significantly associated with emotional symptoms and total SDQ score in RP and SL. Female sex appeared as a protective factor for bruxism, and for clenching and grinding in RP. Furthermore, maternal employment outside the home and white skin color of children were associated with increased prevalence of teeth clenching in SL. Conclusions: Mental health problems were associated with bruxism, with teeth clenching only and grinding at night only. No association was detected between depression and bruxism, neither clenching nor grinding. But it is necessary to be cautious regarding the inferences from some of our results.

Childbearing in adolescence: intergenerational dejà-vu? Evidence from a Brazilian birth cohort

Abstract Background Pregnancy in adolescence tends to repeat over generations. This event has been little studied in middle and low-income societies undergoing a rapid epidemiological transition. To assess this association it is important to adjust for socioeconomic conditions at different points in lifetime. Therefore, the aim of this study is to analyze the independent effect of adolescent childbearing in a generation on its recurrence in the subsequent generation, after adjusting for socioeconomic status at different points in life. Methods The study was conducted on a prospective cohort of singleton liveborn females from the city of Ribeirão Preto, Brazil, evaluated in 1978/79, and their daughters assessed in 2002/04. A total of 1059 mother-daughter pairs were evaluated. The women who had their first childbirth before 20 years of age were considered to be adolescent mothers. The risk of childbearing in adolescence for the daughter was modeled as a function of the occurrence of teenage childbearing in her mother, after adjustment for socio-demographic variables in a Poisson regression model. Results The rate of childbearing during adolescence was 31.4% in 1978/79 and 17.1% in 2002/04. Among the daughters of the 1st generation adolescent mothers, this rate was 26.7%, as opposed to 12.7% among the daughters of non adolescent mothers. After adjustments the risk of adolescent childbearing for the 2nd generation was 35% higher for women whose mothers had been pregnant during adolescence – RR = 1.35 (95% CI 1.04-1.74). Conclusion Adolescent childbearing in the 1st generation was a predictor of adolescent childbearing in the 2nd, regardless of socioeconomic factors determined at different points in lifetime.

Association between particulate matter air pollution and monthly inhalation and nebulization procedures in Ribeirão Preto, São Paulo State, Brazil

The study was designed to investigate the impact of air pollution on monthly inhalation/nebulization procedures in Ribeirão Preto, São Paulo State, Brazil, from 2004 to 2010. To assess the relationship between the procedures and particulate matter (PM10) a Bayesian Poisson regression model was used, including a random factor that captured extra-Poisson variability between counts. Particulate matter was associated with the monthly number of inhalation/nebulization procedures, but the inclusion of covariates (temperature, precipitation, and season of the year) suggests a possible confounding effect. Although other studies have linked particulate matter to an increasing number of visits due to respiratory morbidity, the results of this study suggest that such associations should be interpreted with caution.

Socioeconomic and psychosocial predictors of dental healthcare use among Brazilian preschool children

Abstract Background Disparities in utilization of oral healthcare services have been attributed to socioeconomic and individual behavioral factors. Parents’ socioeconomic status, demographics, schooling, and perceptions of oral health may influence their children’s use of dental services. This cross-sectional study assessed the relationships between socioeconomic and psychosocial factors and the utilization of dental health services by children aged 1–5 years. Methods Data were collected through clinical exams and a structured questionnaire administered during the National Day of Children’s Vaccination. A Poisson regression model was used to estimate prevalence ratios and 95% confidence intervals. Results Data were collected from a total of 478 children. Only 112 (23.68%) were found to have visited a dentist; 67.77% of those had seen the dentist for preventive care. Most (63.11%) used public rather than private services. The use of dental services varied according to parental socioeconomic status; children from low socioeconomic backgrounds and those whose parents rated their oral health as “poor” used dental services less frequently. The reason for visiting the dentist also varied with socioeconomic status, in that children of parents with poor socioeconomic status and who reported their child’s oral health as “fair/poor” were less likely to have visited the dentist for preventive care. Conclusion This study demonstrated that psychosocial and socioeconomic factors are important predictors of the utilization of dental care services.