On a log-symmetric quantile tobit model applied to female labor supply data.

The study of female labor supply has been a topic of relevance in the economic literature. Generally, the data are left-censored and the classic tobit model has been extensively used in the modeling strategy. This model, however, assumes normality for the error distribution and is not recommended for data with positive skewness, heavy-tails and heteroscedasticity, as is the case of female labor supply data. Moreover, it is well-known that the quantile regression approach accounts for the influences of different quantiles in the estimated coefficients. We take all these features into account and propose a parametric quantile tobit regression model based on quantile log-symmetric distributions. The proposed method allows one to model data with positive skewness (which is not suitable for the classic tobit model), to study the influence of the quantiles of interest, and to account for heteroscedasticity. The model parameters are estimated by maximum likelihood and a Monte Carlo experiment is performed to evaluate alternative estimators. The new method is applied to two distinct female labor supply data sets. The results indicate that the log-symmetric quantile tobit model fits better the data than the classic tobit model.

[Catastrophic health expenditures: analysis of the association with socioeconomic conditions in Minas Gerais, Brazil]. / Gastos catastróficos em saúde: análise da associação com condições socioeconômicas em Minas Gerais, Brasil.

This study aimed to assess catastrophic health expenditures (CHE) and its association with socioeconomic conditions in 2009, 2011 and 2013 in Minas Gerais, Brazil. A cross-sectional study was carried out with data from the Household Sample Survey. The dependent variable was the CHE in each year of the survey. Expenditures that exceeded 10% and 25% of household income were considered catastrophic. The association between catastrophic health expenditure and independent variables was tested by the Poisson regression. The prevalence of CHE ranged from 9.0% to 11.3% and 18.9% to 24.4% within the limits of 10% and 25%, and 2011 recorded the lowest values. The largest proportion of health expenditure (94%) was related to the acquisition of medicines. The prevalence of CHE was lower among those responsible for the household with 12 or more years of study than those with no formal education. Households with a higher wealth score had, in both limits, lower prevalence of CHE than those of the first quintile. We concluded that health expenditures significantly affected the budget of households in Minas Gerais and the purchase of medicines was the main component of spending. The findings reinforce the role of the Brazilian Unified Health System (SUS) in minimizing CHE and reducing socioeconomic inequalities.

O objetivo deste estudo foi avaliar os gastos catastróficos em saúde (GCS) e sua associação com condições socioeconômicas nos anos de 2009, 2011 e 2013 em Minas Gerais. Realizou-se um estudo transversal com dados da Pesquisa por Amostra de Domicílios. A variável dependente foi o GCS, em cada ano da pesquisa. Foram considerados catastróficos os gastos que ultrapassaram os limites de 10% e 25% da renda familiar. A associação entre o gasto catastrófico e as variáveis independentes foi testada por meio de regressão de Poisson. As prevalências de GCS variaram de 9,0% a 11,3% e 18,9% a 24,4% nos limites de 10% e 25%, sendo que o ano de 2011 apresentou os menores valores. A maior proporção dos gastos com saúde (94%) foi relativa aos gastos com medicamentos. A prevalência de CGS foi menor entre responsáveis pelo domicílio com maior escolaridade quando comparados àqueles sem estudo nos limites de 10% e 25%. Famílias com maior escore de riqueza apresentaram, nos dois limites, prevalência de GCS menores do que aquelas do primeiro quintil. Concluiu-se que os gastos com saúde afetaram significativamente o orçamento das famílias em Minas Gerais, sendo o gasto com medicamentos o principal componente dos gastos. Os achados reforçam o papel do SUS para minimizar o GCS e reduzir as desigualdades socioeconômicas.

Gastos catastróficos em saúde: análise da associação com condições socioeconômicas em Minas Gerais, Brasil / Catastrophic health expenditures: analysis of the association with socioeconomic conditions in Minas Gerais, Brazil

Resumo O objetivo deste estudo foi avaliar os gastos catastróficos em saúde (GCS) e sua associação com condições socioeconômicas nos anos de 2009, 2011 e 2013 em Minas Gerais. Realizou-se um estudo transversal com dados da Pesquisa por Amostra de Domicílios. A variável dependente foi o GCS, em cada ano da pesquisa. Foram considerados catastróficos os gastos que ultrapassaram os limites de 10% e 25% da renda familiar. A associação entre o gasto catastrófico e as variáveis independentes foi testada por meio de regressão de Poisson. As prevalências de GCS variaram de 9,0% a 11,3% e 18,9% a 24,4% nos limites de 10% e 25%, sendo que o ano de 2011 apresentou os menores valores. A maior proporção dos gastos com saúde (94%) foi relativa aos gastos com medicamentos. A prevalência de CGS foi menor entre responsáveis pelo domicílio com maior escolaridade quando comparados àqueles sem estudo nos limites de 10% e 25%. Famílias com maior escore de riqueza apresentaram, nos dois limites, prevalência de GCS menores do que aquelas do primeiro quintil. Concluiu-se que os gastos com saúde afetaram significativamente o orçamento das famílias em Minas Gerais, sendo o gasto com medicamentos o principal componente dos gastos. Os achados reforçam o papel do SUS para minimizar o GCS e reduzir as desigualdades socioeconômicas.

Abstract This study aimed to assess catastrophic health expenditures (CHE) and its association with socioeconomic conditions in 2009, 2011 and 2013 in Minas Gerais, Brazil. A cross-sectional study was carried out with data from the Household Sample Survey. The dependent variable was the CHE in each year of the survey. Expenditures that exceeded 10% and 25% of household income were considered catastrophic. The association between catastrophic health expenditure and independent variables was tested by the Poisson regression. The prevalence of CHE ranged from 9.0% to 11.3% and 18.9% to 24.4% within the limits of 10% and 25%, and 2011 recorded the lowest values. The largest proportion of health expenditure (94%) was related to the acquisition of medicines. The prevalence of CHE was lower among those responsible for the household with 12 or more years of study than those with no formal education. Households with a higher wealth score had, in both limits, lower prevalence of CHE than those of the first quintile. We concluded that health expenditures significantly affected the budget of households in Minas Gerais and the purchase of medicines was the main component of spending. The findings reinforce the role of the Brazilian Unified Health System (SUS) in minimizing CHE and reducing socioeconomic inequalities.

Bayesian inference for the log-symmetric autoregressive conditional duration model.

This paper adapts Hamiltonian Monte Carlo methods for application in log-symmetric autoregressive conditional duration models. These recent models are based on a class of log-symmetric distributions. In this class, it is possible to model both median and skewness of the duration time distribution. We use the Bayesian approach to estimate the model parameters of some log-symmetric autoregressive conditional duration models and evaluate their performance using a Monte Carlo simulation study. The usefulness of the estimation methodology is demonstrated by analyzing a high frequency financial data set from the German DAX of 2016.

Modeling Mortality Based on Pollution and Temperature Using a New Birnbaum-Saunders Autoregressive Moving Average Structure with Regressors and Related-Sensors Data.

Environmental agencies are interested in relating mortality to pollutants and possible environmental contributors such as temperature. The Gaussianity assumption is often violated when modeling this relationship due to asymmetry and then other regression models should be considered. The class of Birnbaum-Saunders models, especially their regression formulations, has received considerable attention in the statistical literature. These models have been applied successfully in different areas with an emphasis on engineering, environment, and medicine. A common simplification of these models is that statistical dependence is often not considered. In this paper, we propose and derive a time-dependent model based on a reparameterized Birnbaum-Saunders (RBS) asymmetric distribution that allows us to analyze data in terms of a time-varying conditional mean. In particular, it is a dynamic class of autoregressive moving average (ARMA) models with regressors and a conditional RBS distribution (RBSARMAX). By means of a Monte Carlo simulation study, the statistical performance of the new methodology is assessed, showing good results. The asymmetric RBSARMAX structure is applied to the modeling of mortality as a function of pollution and temperature over time with sensor-related data. This modeling provides strong evidence that the new ARMA formulation is a good alternative for dealing with temporal data, particularly related to mortality with regressors of environmental temperature and pollution.

The role of VES-13 to identify limited life expectancy in older adults in primary healthcare settings.

OBJECTIVE: To investigate the potential role of the Vulnerable Elders Survey to identify older adults with limited life expectancy in primary healthcare settings. METHOD: This cross-sectional study was performed in all (nine) healthcare units in Jatai, Goiás (Brazil) from July to December 2018. A sample size of 407 older adults was obtained considering an older population (≥ 60 years old). Participants answered a questionnaire about sociodemographic and clinical characteristics, including the Vulnerable Elders Survey and the Suemoto index. We tested the association between limited life expectancy and the Vulnerable Elders Survey using multiple logistic regression analysis. RESULTS: The mean age was 68.9 ± 6.6 yo, and 58.0% were women. The mean score of the Vulnerable Elders Survey was 2.0 ± 2.2, the mean score of Suemoto index was 31.5 ± 21.1%, and 17.2% had limited life expectancy. The Vulnerable Elders Survey was associated with limited life expectancy (OR = 1.57; p = < 0.0001). CONCLUSION: The Vulnerable Elders Survey was able to identify older adults with limited life expectancy in primary healthcare settings and can play a role in detecting older adults who would not benefit from screening and strict control of chronic diseases.

The role of VES-13 to identify limited life expectancy in older adults in primary healthcare settings / O potencial do VES-13 na identificação da expectativa de vida limitada em idosos na atenção primária à saúde / Potencial del VES-13 para identificar la esperanza de vida limitada de adultos mayores en centros de atención primaria

ABSTRACT Objective To investigate the potential role of the Vulnerable Elders Survey to identify older adults with limited life expectancy in primary healthcare settings. Method This cross-sectional study was performed in all (nine) healthcare units in Jatai, Goiás (Brazil) from July to December 2018. A sample size of 407 older adults was obtained considering an older population (≥ 60 years old). Participants answered a questionnaire about sociodemographic and clinical characteristics, including the Vulnerable Elders Survey and the Suemoto index. We tested the association between limited life expectancy and the Vulnerable Elders Survey using multiple logistic regression analysis. Results The mean age was 68.9 ± 6.6 yo, and 58.0% were women. The mean score of the Vulnerable Elders Survey was 2.0 ± 2.2, the mean score of Suemoto index was 31.5 ± 21.1%, and 17.2% had limited life expectancy. The Vulnerable Elders Survey was associated with limited life expectancy (OR = 1.57; p = < 0.0001). Conclusion The Vulnerable Elders Survey was able to identify older adults with limited life expectancy in primary healthcare settings and can play a role in detecting older adults who would not benefit from screening and strict control of chronic diseases.

RESUMO Objetivo Investigar o potencial do instrumento Vulnerable Elders Survey para identificar idosos com expectativa de vida limitada, em ambientes de atenção primária à saúde. Método Estudo transversal realizado em todas as (nove) unidades de saúde de Jataí, Goiás (Brasil), no período de julho a dezembro de 2018. Obteve-se uma amostra de 407 idosos, considerando uma população ≥ 60 anos. Os participantes responderam a um questionário sobre características sociodemográficas e clínicas, incluindo o Vulnerable Elders Survey e o índice de Suemoto. Testamos a associação entre a expectativa de vida limitada e o Vulnerable Elders Survey usando análise de regressão logística múltipla. Resultados A idade média foi de 68,9 ± 6,6 anos, e 58,0% dos participantes eram mulheres. A pontuação média do Vulnerable Elders Survey foi de 2,0 ± 2,2, a pontuação média do índice de Suemoto foi de 31,5 ± 21,1%, e 17,2% dos participantes tinham expectativa de vida limitada. O Vulnerable Elders Survey foi associado a uma expectativa de vida limitada (OR = 1,57; p = < 0,0001). Conclusão O instrumento Vulnerable Elders Survey foi capaz de identificar idosos com expectativa de vida limitada em ambientes de atenção primária à saúde, além de poder auxiliar na detecção de idosos que não se beneficiariam com a triagem e o controle estrito de doenças crônicas.

RESUMEN Objetivo Investigar el potencial del instrumento Vulnerable Elders Survey para identificar adultos mayores con esperanza de vida limitada en centros de atención primaria. Método Se trata de un estudio transversal realizado en todas las (nueve) unidades sanitarias de Jataí, Goiás (Brasil) de julio a diciembre de 2018. Se consideró una población de ≥ 60 años, de la cual se obtuvo una muestra de 407 adultos mayores. Los participantes respondieron un cuestionario sobre características sociodemográficas y clínicas, incluyendo el Vulnerable Elders Survey y el índice de Suemoto. Se comprobó la asociación entre la esperanza de vida limitada y el Vulnerable Elders Survey, mediante el análisis de regresión logística múltiple. Resultados La edad promedio era de 68,9 ± 6,6 años y el 58,0% de los participantes pertenecía al sexo femenino. La puntuación media del Vulnerable Elders Survey resultó en 2,0 ± 2,2; la puntuación media del índice de Suemoto, 31,5 ± 21,1% y el 17,2% de los participantes tenía una esperanza de vida limitada. El Vulnerable Elders Survey estaba asociado a una esperanza de vida limitada (OR = 1,57; p = < 0,0001). Conclusión El instrumento Vulnerable Elders Survey ha sido capaz de identificar a los adultos mayores con una esperanza de vida limitada en los centros de atención primaria, además de ayudar en la detección de aquellos adultos mayores que no se beneficiarían con el triaje y el control estricto de las enfermedades crónicas.

Catastrophic health expenditure and multimorbidity among older adults in Brazil.

OBJECTIVE: To estimate the relation between catastrophic health expenditure (CHE) and multimorbidity in a national representative sample of the Brazilian population aged 50 year or older. METHODS: This study used data from 8,347 participants of the Estudo Longitudinal de Saúde dos Idosos Brasileiros (ELSI - Brazilian Longitudinal Study of Aging) conducted in 2015-2016. The dependent variable was CHE, defined by the ratio between the health expenses of the adult aged 50 years or older and the household income. The variable of interest was multimorbidity (two or more chronic diseases) and the variable used for stratification was the wealth score. The main analyses were based on multivariate logistic regression. RESULTS: The prevalence of CHE was 17.9% and 7.5%, for expenditures corresponding to 10 and 25% of the household income, respectively. The prevalence of multimorbidity was 63.2%. Multimorbidity showed positive and independent associations with CHE (OR = 1.95, 95%CI 1.67-2.28, and OR = 1.40, 95%CI 1.11-1.76 for expenditures corresponding to 10% and 25%, respectively). Expenditures associated with multimorbidity were higher among those with lower wealth scores. CONCLUSIONS: The results draw attention to the need for an integrated approach of multimorbidity in health services, in order to avoid CHE, particularly among older adults with worse socioeconomic conditions.

Catastrophic health expenditure and multimorbidity among older adults in Brazil / Gastos catastróficos em saúde e multimorbidade entre adultos mais velhos no Brasil

ABSTRACT OBJECTIVE: To estimate the relation between catastrophic health expenditure (CHE) and multimorbidity in a national representative sample of the Brazilian population aged 50 year or older. METHODS: This study used data from 8,347 participants of the Estudo Longitudinal de Saúde dos Idosos Brasileiros (ELSI - Brazilian Longitudinal Study of Aging) conducted in 2015-2016. The dependent variable was CHE, defined by the ratio between the health expenses of the adult aged 50 years or older and the household income. The variable of interest was multimorbidity (two or more chronic diseases) and the variable used for stratification was the wealth score. The main analyses were based on multivariate logistic regression. RESULTS: The prevalence of CHE was 17.9% and 7.5%, for expenditures corresponding to 10 and 25% of the household income, respectively. The prevalence of multimorbidity was 63.2%. Multimorbidity showed positive and independent associations with CHE (OR = 1.95, 95%CI 1.67-2.28, and OR = 1.40, 95%CI 1.11-1.76 for expenditures corresponding to 10% and 25%, respectively). Expenditures associated with multimorbidity were higher among those with lower wealth scores. CONCLUSIONS: The results draw attention to the need for an integrated approach of multimorbidity in health services, in order to avoid CHE, particularly among older adults with worse socioeconomic conditions.

RESUMO OBJETIVO: Estimar a relação entre gasto catastrófico em saúde (GCS) e multimorbidade em amostra nacional representativa da população brasileira com 50 anos de idade ou mais. MÉTODOS: Foram utilizados dados de 8.347 participantes do Estudo Longitudinal da Saúde dos Idosos Brasileiros (2015-2016). A variável dependente foi o GCS, definido pela razão entre as despesas com saúde do adulto de 50 anos ou mais e a renda domiciliar. A variável de interesse foi a multimorbidade (duas ou mais doenças crônicas), e a variável utilizada para estratificação foi o escore de riqueza. As principais análises foram baseadas na regressão logística multivariada. RESULTADOS: A prevalçncia de GCS foi de 17,9% e 7,5% para gastos correspondentes a 10% e 25% da renda domiciliar, respectivamente. A prevalçncia da multimorbidade foi de 63,2%. A multimorbidade apresentou associações positivas e independentes com GCS (OR = 1,95, IC95% 1,67-2,28 e OR = 1,40, IC95% 1,11-1,76 para gastos correspondentes a 10% e 25%, respectivamente). Os gastos associados à multimorbidade foram maiores entre aqueles com menor escore de riqueza. CONCLUSÕES: Os resultados chamam atenção para a necessidade de uma abordagem integrada da multimorbidade nos serviços de saúde, de forma a evitar os GCS, particularmente entre adultos mais velhos com piores condições socioeconômicas.

Incorporation of frailties into a cure rate regression model and its diagnostics and application to melanoma data.

Cure rate models have been widely studied to analyze time-to-event data with a cured fraction of patients. Our proposal consists of incorporating frailty into a cure rate model, as an alternative to the existing models to describe this type of data, based on the Birnbaum-Saunders distribution. Such a distribution has theoretical arguments to model medical data and has shown empirically to be a good option for their analysis. An advantage of the proposed model is the possibility to jointly consider the heterogeneity among patients by their frailties and the presence of a cured fraction of them. In addition, the number of competing causes is described by the negative binomial distribution, which absorbs several particular cases. We consider likelihood-based methods to estimate the model parameters and to derive influence diagnostics for this model. We assess local influence on the parameter estimates under different perturbation schemes. Deriving diagnostic tools is needed in all statistical modeling, which is another novel aspect of our proposal. Numerical evaluation of the considered model is performed by Monte Carlo simulations and by an illustration with melanoma data, both of which show its good performance and its potential applications. Particularly, the illustration confirms the importance of statistical diagnostics in the modeling.

Birnbaum-Saunders frailty regression models: Diagnostics and application to medical data.

In survival models, some covariates affecting the lifetime could not be observed or measured. These covariates may correspond to environmental or genetic factors and be considered as a random effect related to a frailty of the individuals explaining their survival times. We propose a methodology based on a Birnbaum-Saunders frailty regression model, which can be applied to censored or uncensored data. Maximum-likelihood methods are used to estimate the model parameters and to derive local influence techniques. Diagnostic tools are important in regression to detect anomalies, as departures from error assumptions and presence of outliers and influential cases. Normal curvatures for local influence under different perturbations are computed and two types of residuals are introduced. Two examples with uncensored and censored real-world data illustrate the proposed methodology. Comparison with classical frailty models is carried out in these examples, which shows the superiority of the proposed model.