Improved Regression Estimation of a Multivariate Relationship with Population Data on the Bivariate Relationship

Regression coefficients specify the partial effect of a regressor on the dependent variable. Sometimes the bivariate or limited multivariate relationship of that regressor variable with the dependent variable is known from population-level data. We show here that such population- level data can be used to reduce variance and bias about estimates of those regression coefficients from sample survey data. The method of constrained MLE is used to achieve these improvements. Its statistical properties are first described. The method constrains the weighted sum of all the covariate-specific associations (partial effects) of the regressors on the dependent variable to equal the overall association of one or more regressors, where the latter is known exactly from the population data. We refer to those regressors whose bivariate or limited multivariate relationships with the dependent variable are constrained by population data as being ‘‘directly constrained.’’ Our study investigates the improvements in the estimation of directly constrained variables as well as the improvements in the estimation of other regressor variables that may be correlated with the directly constrained variables, and thus ‘‘indirectly constrained’’ by the population data. The example application is to the marital fertility of black versus white women. The difference between white and black women’s rates of marital fertility, available from population-level data, gives the overall association of race with fertility. We show that the constrained MLE technique both provides a far more powerful statistical test of the partial effect of being black and purges the test of a bias that would otherwise distort the estimated magnitude of this effect. We find only trivial reductions, however, in the standard errors of the parameters for indirectly constrained regressors.

Spatial analysis of egg distribution and geographic changes in the spawning habitat of the Brazilian sardine Sardinella brasiliensis

This paper establishes the spawning habitat of the Brazilian sardine Sardinella brasiliensis and investigates the spatial variability of egg density and its relation with oceanographic conditions in the shelf of the south-east Brazil Bight (SBB). The spawning habitats of S. brasiliensis have been defined in terms of spatial models of egg density, temperature-salinity plots, quotient (Q) analysis and remote sensing data. Quotient curves (Q(C)) were constructed using the geographic distribution of egg density, temperature and salinity from samples collected during nine survey cruises between 1976 and 1993. The interannual sea surface temperature (SST) variability was determined using principal component analysis on the SST anomalies (SSTA) estimated from remote sensing data over the period between 1985 and 2007. The spatial pattern of egg occurrences in the SBB indicated that the largest concentration occurred between Paranagua and Sao Sebastiao. Spawning habitat expanded and contracted during the years, fluctuating around Paranagua. In January 1978 and January 1993, eggs were found nearly everywhere along the inner shelf of the SBB, while in January 1988 and 1991 spawning had contracted to their southernmost position. The SSTA maps for the spawning periods showed that in the case of habitat expansion (1993 only) anomalies over the SBB were zero or slightly negative, whereas for the contraction period anomalies were all positive. Sardinella brasiliensis is capable of exploring suitable spawning sites provided by the entrainment of the colder and less-saline South Atlantic Central Water onto the shelf by means of both coastal wind-driven (to the north-east of the SBB) and meander-induced (to the south-west of the SBB) upwelling.

Investigating South American biogeographic history using patterns of skull shape variation on Cerdocyon thous (Mammalia: Canidae)

Patterns of geographic variation of the canid Cerdocyon thous have historically been obscured by its remarkable intraspecific morphological variability. The observed distribution is highly associated with phytophysiognomy, a feature considered highly dynamic along geological time. In the present study, we tested whether vegetation distribution during the Holocene Glacial Maximum of South America (HGM) explains the patterns of morphological variation within Cerdocyon thous. The species was divided in groups according to paleohabitats that could support their presence during the HGM, and then tested for differences in skull morphometrics. The results obtained demonstrate that the climatic changes during the HGM influenced the population structure of this species, resulting in the establishment of geographical groups with different degrees of morphological cohesion. Higher morphological cohesion found in the Northern group might be explained by the marked discontinuity between its geographical range and the rest of the species`distribution. The Eastern and Southern morphological divergence is less striking and, although this could be related to past vegetation distribution, the disappearance of those barriers leads to a population structure that could be slowly breaking down. (C) 2009 The Linnean Society of London, Biological Journal of the Linnean Society, 2009, 98, 77-84.

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.

Dropouts or Discontinuity of the Treatment of Tuberculosis in Rio Branco, Acre

This research investigates the factors related to the discontinuity of the treatment of tuberculosis in Rio Branco-Acre. To the fulfillment of this research, a contribution to ethnography has been adopted, for the successful apprehension of the reality to be studied. The research has been developed in two mapping steps: on the first, a search for information on the SINAN (System of National Injuries Notification - Sistema de Notificacao de Agravos Nacionais) and on the Municipal Coordination of the Tuberculosis Program databases was taken; the second aimed to record facts from the observation of the care given on a health care unit, which serves assistance to tuberculosis carriers in treatment, and the interviews of the elected subjects. On the analysis of the observations, narrative and interview collection, it was observed that the professionals of health services label some people as auspicious to discontinue the treatment and don't consider the different ways of life on the approach of their patients, complicating the formation of the bond and favoring the discontinuity. It was also identified people treating for tuberculosis that had many ways of dealing with the limitations generated by the disease, such as restrictions for the work, among others, and people that discontinued the treatment took in consideration their system of beliefs and values, as well as the perception of health/disease, due to the feeling of cure when the treatment was interrupted.

Contextual and individual inequalities in dental pain prevalence among Brazilian adults and elders

This study aimed to assess the prevalence of dental pain among adults and older people living in Brazil's State capitals. Information was gathered from the Telephone Survey Surveillance System for Risk and Protective Factors for Chronic Diseases (VIGITEL) in 2009 (n = 54,367). Dental pain was the outcome. Geographic region, age, gender, race, schooling, private health coverage, smoking, and soft drink consumption were the explanatory variables. Multilevel Poisson regression models were performed. Prevalence of dental pain was 15.2%; Macapa and Sao Luis had prevalence rates greater than 20%; all capitals in the South and Southeast, plus Cuiaba, Campo Grande, Maceio, Recife, and Natal had prevalence rates less than 15%. Factors associated with increased prevalence of dental pain were the North and Northeast regions, female gender, black/brown skin color, lack of private health insurance, smoking, and soft drink consumption. Dental pain is a public health problem that should be monitored by health surveillance systems.

Estimation and diagnostics for heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions

An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures of skew-normal (SMSN) distributions is developed. This novel class of models provides a useful generalization of the heteroscedastic symmetrical nonlinear regression models (Cysneiros et al., 2010), since the random term distributions cover both symmetric as well as asymmetric and heavy-tailed distributions such as skew-t, skew-slash, skew-contaminated normal, among others. A simple EM-type algorithm for iteratively computing maximum likelihood estimates of the parameters is presented and the observed information matrix is derived analytically. In order to examine the performance of the proposed methods, some simulation studies are presented to show the robust aspect of this flexible class against outlying and influential observations and that the maximum likelihood estimates based on the EM-type algorithm do provide good asymptotic properties. Furthermore, local influence measures and the one-step approximations of the estimates in the case-deletion model are obtained. Finally, an illustration of the methodology is given considering a data set previously analyzed under the homoscedastic skew-t nonlinear regression model. (C) 2012 Elsevier B.V. All rights reserved.

Prevalence, geographic and seasonal distribution of protozoan and myxozoan parasites of jau (Zungaro jahu)

Adriano E.A., Ceccarelli P.S., Silva M.R.M. & Maia A.A. M. 2012. [Prevalence, geographic and seasonal distribution of protozoan and myxozoan parasites of jau (Zungaro jahu) in the Pantanal of Mato Grosso, Brazil.] Prevalencia, distribuicao geografica e sazonal de protozoarios e mixozoarios parasitos de jau (Zungaro jahu) no Pantanal Matogrossense. Pesquisa Veterinaria Brasileira 32(12):1341-1344. Departamento de Ciencias Basicas, Faculdade de Zootecnia e Engenharia de Alimentos, Universidade de Sao Paulo, Av. Duque de Caxias Norte 225, Pirassununga, SP 13635-900, Brazil. E-mail: antomaia@usp.br In a study carried out in the Pantanal of Mato Grosso, Brazil, the prevalence, geographic and seasonal distribution of protozoan and myxozoan parasites of Zungaro jahu was evaluated. The fish were captured in the southern region of Pantanal Mato-grossense (Aquidauana, Miranda and Paraguay rivers) in 2001, 2002 and 2003, in the central region (Pantanal National Park - PARNA Pantanal) in 2003, 2004, 2005 and 2008, and in the northern region (Cuiaba and Manso rivers, in the municipality of Nobres) in 2003, 2004 and 2005. Trichodina sp. was identified parasitized skin and gills of jau in the three regions studied. Epistylis sp. parasitized skin and Cryptobia sp. the gills and were restricted to the Central region, whilst Ichthyophthirius multifiliis parasitized skin in the three regions studied. The occurrence of myxozoans was also observed: Myxobolus cordeiroi parasitized several organs and Henneguya sp. parasitized the gills of jau in the three regions studied.

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.

Local power properties of some asymptotic tests in symmetric linear regression models

In this paper we obtain asymptotic expansions, up to order n(-1/2) and under a sequence of Pitman alternatives, for the nonnull distribution functions of the likelihood ratio, Wald, score and gradient test statistics in the class of symmetric linear regression models. This is a wide class of models which encompasses the t model and several other symmetric distributions with longer-than normal tails. The asymptotic distributions of all four statistics are obtained for testing a subset of regression parameters. Furthermore, in order to compare the finite-sample performance of these tests in this class of models, Monte Carlo simulations are presented. An empirical application to a real data set is considered for illustrative purposes. (C) 2011 Elsevier B.V. All rights reserved.

Error Autocorrelation and Linear Regression for Temperature-Based Evapotranspiration Estimates Improvement

Estimates of evapotranspiration on a local scale is important information for agricultural and hydrological practices. However, equations to estimate potential evapotranspiration based only on temperature data, which are simple to use, are usually less trustworthy than the Food and Agriculture Organization (FAO)Penman-Monteith standard method. The present work describes two correction procedures for potential evapotranspiration estimates by temperature, making the results more reliable. Initially, the standard FAO-Penman-Monteith method was evaluated with a complete climatologic data set for the period between 2002 and 2006. Then temperature-based estimates by Camargo and Jensen-Haise methods have been adjusted by error autocorrelation evaluated in biweekly and monthly periods. In a second adjustment, simple linear regression was applied. The adjusted equations have been validated with climatic data available for the Year 2001. Both proposed methodologies showed good agreement with the standard method indicating that the methodology can be used for local potential evapotranspiration estimates.

The objectives of the US Exploring Expedition's circumnavigation (1838-1842): longitude, nautical charting and the establishment of modern geographic coordinates

This article analyzes the main objectives of the scientific voyage to circumnavigate the earth, undertaken by the United States from 1838 to 1842. Charting was one of the most important of the scientific and strategic goals of the exploratory voyage. The initiative for the undertaking was the search for exact positioning on the high seas after the establishment of the longitude system, when nautical charts and maps from various countries were compared, and other, new ones were drawn. The United States participated in this international effort, leading to the creation of its own cartographic system.

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.

Examination of the performance of different pointwise linear regression progression criteria to detect glaucomatous visual field change

Background: We aimed to investigate the performance of five different trend analysis criteria for the detection of glaucomatous progression and to determine the most frequently and rapidly progressing locations of the visual field. Design: Retrospective cohort. Participants or Samples: Treated glaucoma patients with =8 Swedish Interactive Thresholding Algorithm (SITA)-standard 24-2 visual field tests. Methods: Progression was determined using trend analysis. Five different criteria were used: (A) =1 significantly progressing point; (B) =2 significantly progressing points; (C) =2 progressing points located in the same hemifield; (D) at least two adjacent progressing points located in the same hemifield; (E) =2 progressing points in the same Garway-Heath map sector. Main Outcome Measures: Number of progressing eyes and false-positive results. Results: We included 587 patients. The number of eyes reaching a progression endpoint using each criterion was: A = 300 (51%); B = 212 (36%); C = 194 (33%); D = 170 (29%); and E = 186 (31%) (P = 0.03). The numbers of eyes with positive slopes were: A = 13 (4.3%); B = 3 (1.4%); C = 3 (1.5%); D = 2 (1.1%); and E = 3 (1.6%) (P = 0.06). The global slopes for progressing eyes were more negative in Groups B, C and D than in Group A (P = 0.004). The visual field locations that progressed more often were those in the nasal field adjacent to the horizontal midline. Conclusions: Pointwise linear regression criteria that take into account the retinal nerve fibre layer anatomy enhances the specificity of trend analysis for the detection glaucomatous visual field progression.