Analyse quantitative de la carrière criminelle des internautes effectuant du leurre d’enfants

Objectifs: L’objectif principal de ce mémoire consiste à comprendre les caractéristiques des carrières criminelles d’individus connus de la police pour avoir perpétré une infraction de leurre d’enfants sur Internet. Aussi, par une analyse typologique à l’aide des antécédents criminels, il sera possible d’établir une typologie d’individus ayant leurré des enfants sur Internet. Également, il sera question de vérifier s’il y a un lien entre les caractéristiques des antécédents criminels de ces individus sur la perpétration de l’agression sexuelle hors ligne. Méthodologie: Provenant de données officielles de la communauté policière du Québec, l’échantillon comprend les parcours de criminels ayant perpétré une infraction de leurre d’enfants sur Internet. Des analyses descriptives en lien avec les différents paramètres de la carrière criminelle seront effectuées. Ensuite, des tests de moyenne et une analyse de régression Cox permettront de vérifier la présence ou non d’un lien statistique entre les caractéristiques des antécédents criminels des individus connus de la police pour leurre d’enfants sur Internet et le passage à l’acte physique. Résultats: Les analyses ont montré que la majorité des sujets n’avaient aucun antécédent judiciaire. Pour la plupart, le leurre d’enfants est le crime le plus grave perpétré au cours de leur carrière criminelle. Trois catégories d’individus ont été décelées : les amateurs, les spécialistes et les généralistes. Ce sont les individus polymorphes ayant une carrière criminelle plus grave et plus longue qui sont portés à agresser sexuellement avant le leurre. Cependant, ce sont des individus spécialisés ayant une importante proportion de délits sexuels dans leurs antécédents criminels qui ont plus de chance d’agresser sexuellement suite à l’exploitation sexuelle sur Internet.

Excessive blood pressure increase with exercise and risk of all-cause mortality and cardiac events

The association of an excessive blood pressure increase with exercise (EBPIE) on cardiovascular outcomes remains controversial. We sought to assess its impact on the risk of all-cause mortality and major cardiac events in patients with known or suspected coronary artery disease (CAD) referred for stress testing. Exercise echocardiography was performed in 10,047 patients with known or suspected CAD. An EBPIE was defined as an increase in systolic blood pressure with exercise ≥80 mmHg. The endpoints were all-cause mortality and major cardiac events (MACE), including cardiac death or nonfatal myocardial infarction (MI). Overall, 573 patients exhibited an EBPIE during the tests. Over a mean follow-up of 4.8 years, there were 1,950 deaths (including 725 cardiac deaths), 1,477 MI, and 1,900 MACE. The cumulative 10-year rates of all-cause mortality, cardiac death, nonfatal MI and MACE were 32.9%, 13.1%, 26,9% and 33% in patients who did not develop an EBPIE vs. 18.9%, 4.7%, 17.5% and 20.7% in those experiencing an EBPIE, respectively (p <0.001 for all comparisons). In Cox regression analyses, an EBPIE remained predictive of all-cause mortality (hazard ratio [HR] 0.73, 95% confidence interval [CI] 0.59-0.91, p = 0.004), cardiac death (HR 0.67, 95% CI 0.46-0.98, p = 0.04), MI (HR 0.67, 95% CI 0.52-0.86, p = 0.002), and MACE (HR 0.69, 95% CI 0.56-0.86, p = 0.001). An EBPIE was associated with a significantly lower risk of mortality and MACE in patients with known or suspected CAD referred for stress testing.

Ceramic-veneered zirconia frameworks in full-arch implant rehabilitations: A 6-month to 5-year retrospective cohort study

Purpose: This was a retrospective cohort study designed to evaluate the clinical performance of ceramicveneered zirconia frameworks. Materials and Methods: Patients were recruited according to defined inclusion criteria. All patients were checked every 4 months from the time of definitive rehabilitation. At the end of 2013, all patients were rescheduled and rechecked for study purposes. The restorative procedures assessment was performed by previously established methods. The primary outcomes were the survival and success rates of the prosthesis. Descriptive statistics were used for the patient's demographics, implant distribution, and occurrence of complications. To study the survival and success of the prostheses, a Cox Regression analysis was used with a model constructed in a forward conditional stepwise mode. Predictive variables were included in the model, and adjusted survival curves were obtained for each outcome. Results: From 2008 to 2013, 75 patients were rehabilitated with 92 implant-supported, screw-retained, full-arch ceramic-veneered zirconia framework rehabilitations. The range of follow-up was between 6 months and 5 years. From the 92 full implant-supported screw-retained full-arch rehabilitations, Cox regression analysis indicated that within a 5-year time frame, the probability of framework fracture, major chipping, minor chipping, or any of the former combined to occur was 17.6%, 46.5%, 69.2%, and 90.5%, respectively. Conclusion: Results suggest zirconia as a suitable material for framework structure in implant-supported, full-arch rehabilitations. However, it experiences a high incidence of technical complications, mainly due to ceramic chipping. Further clinical studies should aim to ascertain the effects of clinical features and manufacturing procedures on the survival rates of these prostheses. © 2016 by Quintessence Publishing Co Inc.

Analyse quantitative de la carrière criminelle des internautes effectuant du leurre d’enfants

Objectifs: L’objectif principal de ce mémoire consiste à comprendre les caractéristiques des carrières criminelles d’individus connus de la police pour avoir perpétré une infraction de leurre d’enfants sur Internet. Aussi, par une analyse typologique à l’aide des antécédents criminels, il sera possible d’établir une typologie d’individus ayant leurré des enfants sur Internet. Également, il sera question de vérifier s’il y a un lien entre les caractéristiques des antécédents criminels de ces individus sur la perpétration de l’agression sexuelle hors ligne. Méthodologie: Provenant de données officielles de la communauté policière du Québec, l’échantillon comprend les parcours de criminels ayant perpétré une infraction de leurre d’enfants sur Internet. Des analyses descriptives en lien avec les différents paramètres de la carrière criminelle seront effectuées. Ensuite, des tests de moyenne et une analyse de régression Cox permettront de vérifier la présence ou non d’un lien statistique entre les caractéristiques des antécédents criminels des individus connus de la police pour leurre d’enfants sur Internet et le passage à l’acte physique. Résultats: Les analyses ont montré que la majorité des sujets n’avaient aucun antécédent judiciaire. Pour la plupart, le leurre d’enfants est le crime le plus grave perpétré au cours de leur carrière criminelle. Trois catégories d’individus ont été décelées : les amateurs, les spécialistes et les généralistes. Ce sont les individus polymorphes ayant une carrière criminelle plus grave et plus longue qui sont portés à agresser sexuellement avant le leurre. Cependant, ce sont des individus spécialisés ayant une importante proportion de délits sexuels dans leurs antécédents criminels qui ont plus de chance d’agresser sexuellement suite à l’exploitation sexuelle sur Internet.

Uma caracterização dos imigrantes no distrito de Évora

Uma vez que existe uma grande necessidade de se obter um maior conhecimento das comunidades imigrantes residentes no Distrito, este trabalho tem como principal objectivo caracterizar a população de imigrantes comunitários residentes no distrito de Évora. Em particular, procuramos analisar os casamentos realizados não só entre os não nacionais e portugueses, bem como entre os nãos nacionais entre si. Consideramos os 354 imigrantes que constituem os imigrantes comunitários inscritos legalmente nos Serviços Estrangeiros e Fronteiras de Évora entre 2006 a 2009. Por outro lado, analisamos, para o mesmo período, os casamentos dos imigrantes que casaram com os portugueses num total de 165 indivíduos. Começamos por levar a efeito uma investigação básica de tipo descritivo para uma caracterização dos imigrantes relativamente a diferentes variáveis e investigamos algumas associações entre elas via tabelas de contingência. Refira-se que a maioria dos imigrantes é do sexo feminino, sendo a nacionalidade mais representativa a brasileira. Com base no modelo de regressão de Cox identificamos factores de risco e diferentes perfis associados à rotura do casamento. Mostramos que há evidência estatística para considerar que um menor nível de escolaridade, o pertencer a um país da União Europeia e o ter entrado à procura de trabalho são níveis de factores que aumentam o risco de rotura do casamento. Analisam-se, ainda, de uma forma crítica, a abordagem paramétrica, procurando modelar os dados através dos modelos Exponencial, Weibull, Lognormal e Log-logístico. ABSTRACT: There is a need to obtain a greater understanding of immigrant communities in the district; this work has as main objective to characterize the population of immigrant community residing in the district of Évora. ln particular, we analyze not only marriages between Portuguese and non-nationals, as well as among non-nationals among themselves. We consider the 354 immigrants who are legally registered immigrants in the Community Service of Foreigners and Frontiers of Évora, from 2006 to 2009. Moreover, we analyze, for the same period, the marriages of immigrants who intermarried with the Portuguese for a total of 165 individuals. We start by carrying out a basic descriptive research in order to characterize the immigrants in relation to several variables and investigated some associations between them by contingency tables. It should be noted that most immigrants are women, and the more representative the Brazilian nationality. Based on the Cox regression model, were possible to identify risk factors and identify profiles of high and low risk associated with the rupture of the marriage. We show that there is statistical evidence to conclude that a less educated levels, belonging to a country inside the European Union and have gone looking for work are factors that increase the risk of rupture of the marriage. The parametric approach is analyzed also, in a critical way, seeking to model the data using exponential, Weibull, Lognormal and Log-logistic.

Assessing time-by-covariate interactions in Cox proportional hazards regression models using cubic spline functions

This dissertation develops and explores the methodology for the use of cubic spline functions in assessing time-by-covariate interactions in Cox proportional hazards regression models. These interactions indicate violations of the proportional hazards assumption of the Cox model. Use of cubic spline functions allows for the investigation of the shape of a possible covariate time-dependence without having to specify a particular functional form. Cubic spline functions yield both a graphical method and a formal test for the proportional hazards assumption as well as a test of the nonlinearity of the time-by-covariate interaction. Five existing methods for assessing violations of the proportional hazards assumption are reviewed and applied along with cubic splines to three well known two-sample datasets. An additional dataset with three covariates is used to explore the use of cubic spline functions in a more general setting. ^

Age -period -cohort analysis: An extension of Cox's lifetable regression with time -dependent covariates

It is well known that an identification problem exists in the analysis of age-period-cohort data because of the relationship among the three factors (date of birth + age at death = date of death). There are numerous suggestions about how to analyze the data. No one solution has been satisfactory. The purpose of this study is to provide another analytic method by extending the Cox's lifetable regression model with time-dependent covariates. The new approach contains the following features: (1) It is based on the conditional maximum likelihood procedure using a proportional hazard function described by Cox (1972), treating the age factor as the underlying hazard to estimate the parameters for the cohort and period factors. (2) The model is flexible so that both the cohort and period factors can be treated as dummy or continuous variables, and the parameter estimations can be obtained for numerous combinations of variables as in a regression analysis. (3) The model is applicable even when the time period is unequally spaced.^ Two specific models are considered to illustrate the new approach and applied to the U.S. prostate cancer data. We find that there are significant differences between all cohorts and there is a significant period effect for both whites and nonwhites. The underlying hazard increases exponentially with age indicating that old people have much higher risk than young people. A log transformation of relative risk shows that the prostate cancer risk declined in recent cohorts for both models. However, prostate cancer risk declined 5 cohorts (25 years) earlier for whites than for nonwhites under the period factor model (0 0 0 1 1 1 1). These latter results are similar to the previous study by Holford (1983).^ The new approach offers a general method to analyze the age-period-cohort data without using any arbitrary constraint in the model. ^

Probabilistic methods for seasonal forecasting in a changing climate: Cox-type regression models.

For climate risk management, cumulative distribution functions (CDFs) are an important source of information. They are ideally suited to compare probabilistic forecasts of primary (e.g. rainfall) or secondary data (e.g. crop yields). Summarised as CDFs, such forecasts allow an easy quantitative assessment of possible, alternative actions. Although the degree of uncertainty associated with CDF estimation could influence decisions, such information is rarely provided. Hence, we propose Cox-type regression models (CRMs) as a statistical framework for making inferences on CDFs in climate science. CRMs were designed for modelling probability distributions rather than just mean or median values. This makes the approach appealing for risk assessments where probabilities of extremes are often more informative than central tendency measures. CRMs are semi-parametric approaches originally designed for modelling risks arising from time-to-event data. Here we extend this original concept beyond time-dependent measures to other variables of interest. We also provide tools for estimating CDFs and surrounding uncertainty envelopes from empirical data. These statistical techniques intrinsically account for non-stationarities in time series that might be the result of climate change. This feature makes CRMs attractive candidates to investigate the feasibility of developing rigorous global circulation model (GCM)-CRM interfaces for provision of user-relevant forecasts. To demonstrate the applicability of CRMs, we present two examples for El Ni ? no/Southern Oscillation (ENSO)-based forecasts: the onset date of the wet season (Cairns, Australia) and total wet season rainfall (Quixeramobim, Brazil). This study emphasises the methodological aspects of CRMs rather than discussing merits or limitations of the ENSO-based predictors.

Regression models for bivariate survival data

Multivariate lifetime data arise in various forms including recurrent event data when individuals are followed to observe the sequence of occurrences of a certain type of event; correlated lifetime when an individual is followed for the occurrence of two or more types of events, or when distinct individuals have dependent event times. In most studies there are covariates such as treatments, group indicators, individual characteristics, or environmental conditions, whose relationship to lifetime is of interest. This leads to a consideration of regression models.The well known Cox proportional hazards model and its variations, using the marginal hazard functions employed for the analysis of multivariate survival data in literature are not sufficient to explain the complete dependence structure of pair of lifetimes on the covariate vector. Motivated by this, in Chapter 2, we introduced a bivariate proportional hazards model using vector hazard function of Johnson and Kotz (1975), in which the covariates under study have different effect on two components of the vector hazard function. The proposed model is useful in real life situations to study the dependence structure of pair of lifetimes on the covariate vector . The well known partial likelihood approach is used for the estimation of parameter vectors. We then introduced a bivariate proportional hazards model for gap times of recurrent events in Chapter 3. The model incorporates both marginal and joint dependence of the distribution of gap times on the covariate vector . In many fields of application, mean residual life function is considered superior concept than the hazard function. Motivated by this, in Chapter 4, we considered a new semi-parametric model, bivariate proportional mean residual life time model, to assess the relationship between mean residual life and covariates for gap time of recurrent events. The counting process approach is used for the inference procedures of the gap time of recurrent events. In many survival studies, the distribution of lifetime may depend on the distribution of censoring time. In Chapter 5, we introduced a proportional hazards model for duration times and developed inference procedures under dependent (informative) censoring. In Chapter 6, we introduced a bivariate proportional hazards model for competing risks data under right censoring. The asymptotic properties of the estimators of the parameters of different models developed in previous chapters, were studied. The proposed models were applied to various real life situations.

A fast identification algorithm for Box-Cox transformation based radial basis function neural network

In this letter, a Box-Cox transformation-based radial basis function (RBF) neural network is introduced using the RBF neural network to represent the transformed system output. Initially a fixed and moderate sized RBF model base is derived based on a rank revealing orthogonal matrix triangularization (QR decomposition). Then a new fast identification algorithm is introduced using Gauss-Newton algorithm to derive the required Box-Cox transformation, based on a maximum likelihood estimator. The main contribution of this letter is to explore the special structure of the proposed RBF neural network for computational efficiency by utilizing the inverse of matrix block decomposition lemma. Finally, the Box-Cox transformation-based RBF neural network, with good generalization and sparsity, is identified based on the derived optimal Box-Cox transformation and a D-optimality-based orthogonal forward regression algorithm. The proposed algorithm and its efficacy are demonstrated with an illustrative example in comparison with support vector machine regression.

Improved likelihood inference for the shape parameter in Weibull regression

We obtain adjustments to the profile likelihood function in Weibull regression models with and without censoring. Specifically, we consider two different modified profile likelihoods: (i) the one proposed by Cox and Reid [Cox, D.R. and Reid, N., 1987, Parameter orthogonality and approximate conditional inference. Journal of the Royal Statistical Society B, 49, 1-39.], and (ii) an approximation to the one proposed by Barndorff-Nielsen [Barndorff-Nielsen, O.E., 1983, On a formula for the distribution of the maximum likelihood estimator. Biometrika, 70, 343-365.], the approximation having been obtained using the results by Fraser and Reid [Fraser, D.A.S. and Reid, N., 1995, Ancillaries and third-order significance. Utilitas Mathematica, 47, 33-53.] and by Fraser et al. [Fraser, D.A.S., Reid, N. and Wu, J., 1999, A simple formula for tail probabilities for frequentist and Bayesian inference. Biometrika, 86, 655-661.]. We focus on point estimation and likelihood ratio tests on the shape parameter in the class of Weibull regression models. We derive some distributional properties of the different maximum likelihood estimators and likelihood ratio tests. The numerical evidence presented in the paper favors the approximation to Barndorff-Nielsen`s adjustment.