Non-homogeneous Markov models in the analysis of survival after breast cancer

A cohort of 300 women with breast cancer who were submitted for surgery is analysed by using a non-homogeneous Markov process. Three states are onsidered: no relapse, relapse and death. As relapse times change over time, we have extended previous approaches for a time homogeneous model to a non omogeneous multistate process. The trends of the hazard rate functions of transitions between states increase and then decrease, showing that a changepoint can be considered. Piecewise Weibull distributions are introduced as transition intensity functions. Covariates corresponding to treatments are incorporated in the model multiplicatively via these functions. The likelihood function is built for a general model with k changepoints and applied to the data set, the parameters are estimated and life-table and transition probabilities for treatments in different periods of time are given. The survival probability functions for different treatments are plotted and compared with the corresponding function for the homogeneous model. The survival functions for the various cohorts submitted for treatment are fitted to the mpirical survival functions.     

Exploring racism inside and outside the mathematics classroom in two different contexts: Colombia and USA

We give attention to the racial contexts of mathematics education in Colombia and the USA. We discuss the particularities of these contexts but also explore the how in both contexts Blackness and Black people are relegated to the lower rungs of the social order. In offering this comparative analysis, we call for expanded research on race, racism, and mathematics education in global contexts.     

Self-Sustained Quality of Life Monitoring: The Philippine Social Weather Reports

In the Philippines, measurement of social indicators covering Qualityof Life and other social concerns has been institutionalized by means ofa unique Social Weather Reporting system. The Social Weather Reports arebased on a series of national surveys operated on a self-sustaining,syndicate-cum-omnibus basis by a private research institute whichoperates as an “enterprising non-profit.” The surveys began on asemestral basis in 1986 and have been run quarterly since 1992. Amongtheir regular topics are self-rated poverty, QOL gaining/losing andoptimism/pessimism, victimization by common crimes, satisfactionwith the performance of government institutions and officials, publicopinion on contemporaneous critical issues, and electoral prospects.Since the topics all deal with public issues, subscribers to the SocialWeather Reports are mostly from the public sector, plus some corporateand diplomatic institutions. Access of non-subscribers to the surveyfindings is on a delayed basis; all surveys are archived for publicuse. The most important factors behind the success of the Social WeatherReports have been their consistent focus on indicators of democracy andgovernance and their record in predicting the outcomes of the 1992,1995, and 1998 national elections in the Philippines.     

The Relevance of Organizational Structure to NGOs’ Approaches to the Policy Process

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - NGOs are recognized as active participants in the policy process. There is general agreement that they are agenda setters...     

Bayesian analysis of generalized elliptical semi-parametric models

In this paper, we study the statistical inference based on the Bayesian approach for regression models with the assumption that independent additive errors follow normal, Student-t, slash, contaminated normal, Laplace or symmetric hyperbolic distribution, where both location and dispersion parameters of the response variable distribution include nonparametric additive components approximated by B-splines. This class of models provides a rich set of symmetric distributions for the model error. Some of these distributions have heavier or lighter tails than the normal as well as different levels of kurtosis. In order to draw samples of the posterior distribution of the interest parameters, we propose an efficient Markov Chain Monte Carlo (MCMC) algorithm, which combines Gibbs sampler and Metropolis–Hastings algorithms. The performance of the proposed MCMC algorithm is assessed through simulation experiments. We apply the proposed methodology to a real data set. The proposed methodology is implemented in the R package BayesGESM using the function gesm().     

A SEMIPARAMETRIC HIERARCHICAL METHOD FOR A REGRESSION MODEL WITH AN INTERVAL-CENSORED COVARIATE

A Bayesian framework is proposed for analysing regression models in which one of the covariates is interval‐censored. Such a situation was encountered in an AIDS clinical trial in which the goal was to examine the association between delays in initiating a new treatment after Indinavir failure and the subsequent viral load level of patients at the time of enrolment into the new treatment. The new method uses a mixture of Dirichlet processes allowing all the components in the model to be specified parametrically, except for the distribution of the interval‐censored covariate, which is treated non‐parametrically. The paper explains the proposed method for the linear regression model in detail. The performance of the method is assessed by simulations and illustrated using the AIDS clinical trial.     

Non-parametric estimation with doubly censored data

Data from longitudinal studies in which an initiating event and a subsequent event occur in sequence are called 'doubly censored' data if the time of both events is interval-censored. This paper is concerned with using doubly censored data to estimate the distribution function of the so-called 'duration time', i.e. the elapsed time between the originating event and the subsequent event. The paper proposes a generalization of the Gomez and Lagakos two-step method for the case where both the time to the initiating event and the duration time are continuous. This approach is applied to estimate the AIDS-latency time from a haemophiliacs cohort.     

Reliant behavior in the United States and Japan

Japanese economic success is often attributed to culturally reinforced psychological conditioning that promotes interpersonal reliance, cooperation, and a group interest orientation. This article provides direct experimental evidence on differences in behavior among future business people in the United States and Japan. Utilizing a simple, two person extensive form game of perfect information introduced by Selten (1975), we provide evidence that, contrary to some views, the Japanese can be less reliant on the behavior of others and are more likely to take actions at variance with group welfare in some settings. Thus, popular explanations of Japanese economic achievements may require further exploration.     

A new mixed first-order integer-valued autoregressive process with Poisson innovations

AStA Advances in Statistical Analysis - Integer-valued time series, seen as a collection of observations measured sequentially over time, have been studied with deep notoriety in recent years, with...     

Contribution of mental workload to job stress in industrial workers

This study's central objective is to determine how several individual, organizational and ergonomic factors influence the relationship between job stress and mental workload for workers in an electronics company. A cross-sectional study was made as a test of hypotheses regarding that relationship. The sample is composed of 95 workers, of both sexes, from the electronics industry in the metropolitan zone of Guadalajara, Jalisco, Mexico. Ergonomic conditions were evaluated with the Ergonomic Evaluation List, stress was evaluated by administering the SWS-Survey to groups of subjects, and mental workload was evaluated with the NASA-TLX Workload Index. Using Cochran's and Mantel-Haenzsel statistics, the odds ratio for each of the independent variables was {e}stimated as a risk factor for job stress, and analysis was later conducted by means of logistic regression for those risks found to be significant. Of the 95 worker participants, 26.3% presented a high level of job stress and 17.9% of the workers were found to present high levels of mental workload. The results show that working hours, mental demand, temporal demand, and frustration when faced with a given task may be considered risk factors for job stress.