Towards greater accuracy in individual-tree mortality regression

Background mortality is an essential component of any forest growth and yield model. Forecasts of mortality contribute largely to the variability and accuracy of model predictions at the tree, stand and forest level. In the present study, I implement and evaluate state-of-the-art techniques to increase the accuracy of individual tree mortality models, similar to those used in many of the current variants of the Forest Vegetation Simulator, using data from North Idaho and Montana. The first technique addresses methods to correct for bias induced by measurement error typically present in competition variables. The second implements survival regression and evaluates its performance against the traditional logistic regression approach. I selected the regression calibration (RC) algorithm as a good candidate for addressing the measurement error problem. Two logistic regression models for each species were fitted, one ignoring the measurement error, which is the “naïve” approach, and the other applying RC. The models fitted with RC outperformed the naïve models in terms of discrimination when the competition variable was found to be statistically significant. The effect of RC was more obvious where measurement error variance was large and for more shade-intolerant species. The process of model fitting and variable selection revealed that past emphasis on DBH as a predictor variable for mortality, while producing models with strong metrics of fit, may make models less generalizable. The evaluation of the error variance estimator developed by Stage and Wykoff (1998), and core to the implementation of RC, in different spatial patterns and diameter distributions, revealed that the Stage and Wykoff estimate notably overestimated the true variance in all simulated stands, but those that are clustered. Results show a systematic bias even when all the assumptions made by the authors are guaranteed. I argue that this is the result of the Poisson-based estimate ignoring the overlapping area of potential plots around a tree. Effects, especially in the application phase, of the variance estimate justify suggested future efforts of improving the accuracy of the variance estimate. The second technique implemented and evaluated is a survival regression model that accounts for the time dependent nature of variables, such as diameter and competition variables, and the interval-censored nature of data collected from remeasured plots. The performance of the model is compared with the traditional logistic regression model as a tool to predict individual tree mortality. Validation of both approaches shows that the survival regression approach discriminates better between dead and alive trees for all species. In conclusion, I showed that the proposed techniques do increase the accuracy of individual tree mortality models, and are a promising first step towards the next generation of background mortality models. I have also identified the next steps to undertake in order to advance mortality models further.

Poisson dynamic models. An application to interurban accidents in Spain

In this study we apply count data models to four integer–valued time series related to accidentality in Spanish roads applying both the frequentist and Bayesian approaches. The time series are: number of fatalities, number of fatal accidents, number of killed or seriously injured (KSI) and number of accidents with KSI. The model structure is Poisson regression with first order autoregressive errors. The purpose of the paper is first to sort out the explanatory variables by relevance and second to carry out a prediction exercise for validation.

Use of posterior predictive assessments to evaluate model fit in multilevel logistic regression

Assessing the fit of a model is an important final step in any statistical analysis, but this is not straightforward when complex discrete response models are used. Cross validation and posterior predictions have been suggested as methods to aid model criticism. In this paper a comparison is made between four methods of model predictive assessment in the context of a three level logistic regression model for clinical mastitis in dairy cattle; cross validation, a prediction using the full posterior predictive distribution and two “mixed” predictive methods that incorporate higher level random effects simulated from the underlying model distribution. Cross validation is considered a gold standard method but is computationally intensive and thus a comparison is made between posterior predictive assessments and cross validation. The analyses revealed that mixed prediction methods produced results close to cross validation whilst the full posterior predictive assessment gave predictions that were over-optimistic (closer to the observed disease rates) compared with cross validation. A mixed prediction method that simulated random effects from both higher levels was best at identifying the outlying level two (farm-year) units of interest. It is concluded that this mixed prediction method, simulating random effects from both higher levels, is straightforward and may be of value in model criticism of multilevel logistic regression, a technique commonly used for animal health data with a hierarchical structure.

Factors associated with the prevalence of hypertension and control practices among elderly residents of São Paulo city, Brazil

The aim of this study was to analyze the prevalence of hypertension and control practices among the elderly. The survey analyzed data from 872 elderly people in São Paulo, Brazil, through a cluster sampling, stratified according to education and income. A Poisson multiple regression model checked for the existence of factors associated with hypertension. The prevalence of self-reported hypertension among the elderly was 46.9%. Variables associated with hypertension were self-rated health, alcohol consumption, gender, and hospitalization in the last year, regardless of age. The three most common measures taken to control hypertension, but only rarely, are oral medication, routine salt-free diet and physical activity. Lifestyle and socioeconomic status did not affect the practice of control, but knowledge about the importance of physical activity was higher among those older people with higher education and greater income. The research suggests that health policies that focus on primary care to encourage lifestyle changes among the elderly are necessary.

Práticas de alimentação complementar no primeiro ano de vida e fatores associados

OBJETIVO: Investigar a prevalência de consumo de alimentos complementares e os fatores associados à alimentação complementar oportuna em menores de um ano. MÉTODOS: Participaram do estudo 1 176 crianças, durante a Campanha Nacional de Vacinação de 2003, em São Bernardo do Campo (SP), cujos acompanhantes responderam questionário que incluiu questões sobre a alimentação da criança nas 24 horas precedentes. A estimativa da prevalência de consumo dos alimentos complementares foi realizada por um modelo de regressão logística ajustado por idade; as medianas de introdução de alimentos por análise de sobrevida e os fatores associados à alimentação complementar oportuna por regressão de Poisson com ajuste robusto de variância e seleção hierarquizada de variáveis. RESULTADOS: Observou-se introdução precoce de alimentos complementares: no quarto mês, cerca de um terço das crianças recebiam suco de fruta e um quarto das crianças recebiam mingau, fruta ou sopa, ao passo que a probabilidade de consumir a comida da família aos oito meses foi baixa (48%). A mediana de idade para o consumo de frutas foi de 266 dias (IC95% 256-275), de papa de legumes foi 258 dias (IC95% 250-264) e comida da família, 292 dias (IC 95% 287-303). Os fatores associados ao consumo de alimentos sólidos antes dos seis meses de idade foram: sistema de assistência à saúde; idade materna; trabalho materno e uso de chupeta. CONCLUSÃO: O consumo precoce de alimentos sólidos, um risco potencial para a saúde infantil e para o desenvolvimento de doenças crônicas na idade adulta, evidenciam a necessidade de ações programáticas para reversão deste quadro.

Anemia e deficiência de ferro em pré-escolares da Amazônia Ocidental brasileira: prevalência e fatores associados

Estudo transversal de base populacional que investigou prevalênciasde anemia e fatores associados à anemia, anemia ferropriva e deficiência de ferro entre crianças de 6 a 60 meses da área urbana de dois municípios do Acre, Brasil (N = 624). Dosagens de hemoglobina sanguínea, ferritina e receptor solúvel de transferrina plasmáticas foram realizadas mediante sangue venoso. Condições sócio-econômicas, demográficas e de morbidade foram obtidas por questionário. Razões de prevalências foram calculadas por regressão de Poisson em modelo hierárquico. As prevalências de anemia, anemia ferropriva e deficiência de ferro foram de 30,6%, 20,9% e 43,5%, respectivamente. Menores de 24 meses apresentaram maior risco para anemia, anemia ferropriva e deficiência de ferro. Pertencer ao maior tercil do índice de riqueza conferiu proteção contra anemia ferropriva (RP = 0,62; IC95%: 0,40-0,98). Pertencer ao maior quartil do índice estatura/idade foi protetor contra anemia (0,62; 0,44-0,86) e anemia ferropriva (0,51; 0,33-0,79), e ocorrência recente de diarréia representou risco (anemia: 1,47; 1,12-1,92 e anemia ferropriva: 1,44; 1,03-2,01). A infestação por geohelmintos conferiu risco para anemia, anemia ferropriva e deficiência de ferro.

Inatividade física e fatores associados em adultos, São Paulo, Brasil

OBJETIVO: Analisar prevalências de inatividade física e fatores associados, e exercícios e esportes praticados segundo escolaridade em 2.050 adultos de 18 a 59 anos de idade - Estado de São Paulo, Brasil. MÉTODOS: Estudo transversal de base populacional com amostra estratificada e em múltiplos estágios. A inatividade física global foi aferida pelo International Physical Activity questionary - IPAQ short version, e por questão sobre prática regular de atividade física no lazer. A análise dos dados levou em conta o desenho amostral. RESULTADOS: A prevalência de inatividade física no lazer foi maior entre as mulheres. Já a inatividade física pelo IPAQ foi maior entre os homens. Modelos de regressão múltipla de Poisson indicaram, nos homens, menor inatividade física pelo IPAQ nos solteiros e separados, estudantes e aqueles que não possuíam carro. A inatividade física no lazer foi maior nos homens acima de 40 anos e com menor escolaridade ou apenas estudantes. A inatividade física pelo IPAQ, nas mulheres, foi mais prevalente entre as com maior escolaridade, ocupações menos qualificadas e viúvas; a inatividade física no lazer diminuiu com o aumento da idade e da escolaridade. Entre as modalidades praticadas no lazer, a caminhada foi a mais prevalente nas mulheres e o futebol nos homens. A maioria das modalidades foi diretamente associada à escolaridade; aproximadamente 25% dos indivíduos com mais de 12 anos de estudo praticava caminhada. CONCLUSÕES: Estes resultados sugerem que intervenções e políticas públicas de promoção da atividade física devem considerar diferenças socioeconômicas, de gênero, bem como as modalidades e o contexto em que a atividade física é praticadA

Retardo estatural em menores de cinco anos: um estudo "baseline"

OBJETIVO: Descrever a prevalência e analisar fatores associados ao retardo estatural em menores de cinco anos. MÉTODOS: Estudo “baseline”, que analisou 2.040 menores de cinco anos, verificando possíveis associações entre o retardo estatural (índice altura/idade ≤ 2 escores Z) e variáveis hierarquizadas em seis blocos: socioeconômicas, do domicílio, do saneamento, maternas, biológicas e de acesso aos serviços de saúde. A análise multivariada foi realizada por regressão de Poisson, com opção de erro padrão robusto, obtendo-se as razões de prevalência ajustadas, com IC 95por cento e respectivos valores de significância. RESULTADOS: Entre as variáveis não dicotômicas, houve associação positiva com tipo de teto e número de moradores por cômodo e associação negativa com renda, escolaridade da mãe e peso ao nascer. A análise ajustada indicou ainda como variáveis significantes: abastecimento de água, visita do agente comunitário de saúde, local do parto, internação por diarréia e internação por pneumonia. CONCLUSÃO: Os fatores identificados como de risco para o retardo estatural configuram a multicausalidade do problema, implicando na necessidade de intervenções multisetoriais e multiníveis para o seu controle

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.

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.

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated 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 those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

Hysterectomy fractions in New South Wales, 1971-2006

Hysterectomy fractions by age group for particular periods are of interest for: estimating proper population denominators for calculation of disease and procedure rates affecting the cervix and uterus; estimating the target population for Pap test programs, and response rates; and as a way of displaying the cumulative consequences of hysterectomies in a population. Hysterectomy fractions for populations can be determined by direct inquiry via a representative sample survey, or, as in this study, from prior hysterectomy rates of the cohorts of women which compose each age bracket. Hysterectomy data 1979-93 were obtained from the hospital In-patients Statistics Collection (ISC) which covers both public and private hospitals in NSW. Annual population denominators of women were obtained from Census data. Data were modelled by Poisson regression, using five.-year age group (15-greater than or equal to 85 years), annual period, and five-year birth cohort (APC model). Forward- and back-projection of the period effects were undertaken. The resultant NSW hysterectomy fractions by age and period are consistent with fractions obtained from modelled hysterectomy rates for Western Australia (1980-84), and fractions from national representative sample surveys (1989/90 and 1995) for younger women, but not for women aged greater than or equal to 70 years in 1995, which revealed higher hysterectomy fractions than modelled hysterectomy data would suggest. Hysterectomy fractions for NSW women by five-year age group for quinquennia centred on 1971 to 2006 are provided.

Anthropometric measures in relation to Basal Cell Carcinoma: a longitudinal study

Background: The relationship between anthropometric indices and risk of basal cell carcinoma ( BCC) is largely unknown. We aimed to examine the association between anthropometric measures and development of BCC and to demonstrate whether adherence to World Health Organisation guidelines for body mass index, waist circumference, and waist/ hip ratio was associated with risk of BCC, independent of sun exposure. Methods: Study participants were participants in a community- based skin cancer prevention trial in Nambour, a town in southeast Queensland ( latitude 26 degrees S). In 1992, height, weight, and waist and hip circumferences were measured for all 1621 participants and weight was remeasured at the end of the trial in 1996. Prevalence proportion ratios were calculated using a log- binomial model to estimate the risk of BCC prior to or prevalent in 1992, while Poisson regression with robust error variances was used to estimate the relative risk of BCC during the follow- up period. Results: At baseline, 94 participants had a current BCC, and 202 had a history of BCC. During the 5- year follow- up period, 179 participants developed one or more new BCCs. We found no significant association between any of the anthropometric measures or indices and risk of BCC after controlling for potential confounding factors including sun exposure. There was a suggestion that short- term weight gain may increase the risk of developing BCC for women only. Conclusion: Adherence to World Health Organisation guidelines for body mass index, waist circumference and waist/ hip ratio is not significantly associated with occurrence of basal cell carcinomas of the skin.

Chronic obstructive pulmonary disease in Brazil: mortality and hospitalization trends and rates, 1996-2008

SETTING: Chronic obstructive pulmonary disease (COPD) is the third leading cause of death among adults in Brazil. OBJECTIVE: To evaluate the mortality and hospitalisation trends in Brazil caused by COPD during the period 1996-2008. DESIGN: We used the health official statistics system to obtain data about mortality (1996-2008) and morbidity (1998-2008) due to COPD and all respiratory diseases (tuberculosis: codes A15-16; lung cancer: code C34, and all diseases coded from J40 to 47 in the 10th Revision of the International Classification of Diseases) as the underlying cause, in persons aged 45-74 years. We used the Joinpoint Regression Program log-linear model using Poisson regression that creates a Monte Carlo permutation test to identify points where trend lines change significantly in magnitude/direction to verify peaks and trends. RESULTS: The annual per cent change in age-adjusted death rates due to COPD declined by 2.7% in men (95%CI -3.6 to -1.8) and -2.0% (95%CI -2.9 to -1.0) in women; and due to all respiratory causes it declined by -1.7% (95%CI 2.4 to -1.0) in men and -1.1% (95%CI -1.8 to -0.3) in women. Although hospitalisation rates for COPD are declining, the hospital admission fatality rate increased in both sexes. CONCLUSION: COPD is still a leading cause of mortality in Brazil despite the observed decline in the mortality/hospitalisation rates for both sexes.