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.     

Statistical Inference on a Stochastic Epidemic Model

In this work, we develop statistical inference for the parameters of a discrete-time stochastic SIR epidemic model. We use a Markov chain for describing the dynamic behavior of the epidemic. Specifically, we propose estimators for the contact and removal rates based on the maximum likelihood and martingale methods, and establish their asymptotic distributions. The obtained results are applied in the statistical analysis of the basic reproduction number, a quantity that is useful in establishing vaccination policies. In order to evaluate the population size for which the results are useful, a numerical study is carried out. Finally, a comparison of the maximum likelihood and martingale estimators is conducted by means of Monte Carlo simulations.     

Sources of error in reported childlessness in a continuous British household survey

A recent investigation of the British General Household Survey (GHS) found substantial over-reporting of childlessness in recent years, particularly at older ages. We examine the phenomenon in further detail and find that the principal cause was change in survey procedures. To some extent the bias can be corrected for by using information on own children in the household. Revised fertility histories give period estimates of total fertility that are in close agreement with national vital registration statistics, unlike those based on original fertility histories of recent years. Misreporting in fertility histories dates primarily from administrative changes in the GHS in the years 1998-2000, and particularly from 2003, when the option of laptop self-completion (CASI) was introduced for reporting demographic histories.     

Education as a Positional Good: A Life Satisfaction Approach

In this paper we empirically investigate the direct effects of education on utility. Besides investment aspects of education, the focus is placed on its consumption component and on education positional concerns. We use data from the World Values Survey (WVS) and adopt a life satisfaction approach. First, we find that education shows a significant effect on life satisfaction independent of its effect on income, thus identifying a consumption component of education. Furthermore, given that the contribution of education to individual wellbeing might depend partly on relative position rather than absolute levels, we next study whether education can be considered as a positional good. To this end we analyse the relationship between education and life satisfaction for people in different income groups in which the reference levels of education may differ. Additionally, we control for occupational status since benefits from education could appear via occupational benefits. Our results indicate that the contribution of education to subjective wellbeing is stronger as less people attain a given level of education, thus suggesting that this contribution is partly due to positional concerns.     

The environmental efficiency of well-being: A cross-national analysis

Recent research has conceptualized sustainability as the environmental efficiency of well-being (EWEB). This concept takes into account the benefits societies are able to produce from their demands on the environment. Research along these lines indicates that countries vary widely in the efficiency with which they transform the Earth’s resources into well-being. Here, we take up this finding as a puzzle to be explained. We construct a new measure of EWEB using the ecological footprint per capita (a measure of environmental consumption) and average life satisfaction (a measure of subjective well-being). We draw hypotheses from political economy, modernization, and sustainable consumption theories in the environmental social sciences. Using full information maximum likelihood estimation, we test the effects of climate, political, economic, and social factors on EWEB with a sample of 105 countries. Key findings include a negative quadratic effect of economic development on EWEB, a negative effect of income inequality, and a positive effect of social capital.     

The effect of variability and carryover on average bioequivalence assessment: a simulation study

The purpose of this study was to evaluate the effect of residual variability and carryover on average bioequivalence (ABE) studies performed under a 22 crossover design. ABE is usually assessed by means of the confidence interval inclusion principle. Here, the interval under consideration was the standard 'shortest' interval, which is the mainstream approach in practice. The evaluation was performed by means of a simulation study under different combinations of carryover and residual variability besides of formulation effect and sample size. The evaluation was made in terms of percentage of ABE declaration, coverage and interval precision. As is well known, high levels of variability distort the ABE procedures, particularly its type II error control (i.e. high variabilities make difficult to declare bioequivalence when it holds). The effect of carryover is modulated by variability and is especially disturbing for the type I error control. In the presence of carryover, the risk of erroneously declaring bioequivalence may become high, especially for low variabilities and large sample sizes. We end up with some hints concerning the controversy about pretesting for carryover before performing ABE analysis.     

Design issues for population growth models

We briefly review and discuss design issues for population growth and decline models. We then use a flexible growth and decline model as an illustrative example and apply optimal design theory to find optimal sampling times for estimating model parameters, specific parameters and interesting functions of the model parameters for the model with two real applications. Robustness properties of the optimal designs are investigated when nominal values or the model is mis-specified, and also under a different optimality criterion. To facilitate use of optimal design ideas in practice, we also introduce a website for generating a variety of optimal designs for popular models from different disciplines.     

Modeling wind energy flux by a Birnbaum–Saunders distribution with an unknown shift parameter

In this paper, we discuss a Birnbaum–Saunders distribution with an unknown shift parameter and apply it to wind energy modeling. We describe structural aspects of this distribution including properties, moments, mode and hazard and shape analyses. We also discuss estimation, goodness of fit and diagnostic methods for this distribution. A computational implementation in R language of the obtained results is provided. Finally, we apply such results to two unpublished real wind speed data from Chile, which allows us to show the characteristics of this statistical distribution and to model wind energy flux.