Catalogue of Group Structures for Three-level Fractional Factorial Designs

Taguchi (1959) introduced the concept of split-unit design to sort the factors into different groups depending upon the difficulties involved in changing the levels of factors. Li et al. (1991) renamed it as split-plot design. Chen et al. (1993) have given a catalogue of small designs for two- and three-level fractional factorial designs pertaining to a single type of factors. Aggarwal et al. (1997) have given a catalogue of group structure for two-level fractional factorial designs developed under the concept of split-plot design. In this paper, an algorithm has been developed for generating group structure and possible allocations for various 3^n-k fractional factorial designs.     

Job displacement effects of Canadian immigrants by country of origin and occupation

"Some previous Canadian studies have shown that considering the labor market as a whole and also pooling all immigrants as a group, immigrants do not have any job displacement effects on the Canadian born. This study presents some new evidence. It disaggregates immigrants by country of origin and by occupation groups and provides an analysis of job displacement effects of immigrants on the native-born Canadians by these dimensions. The study finds that (1) U.S. immigrants and the Canadians are substitutes [for] competing groups in the labor market and the effect is quite significant; (2) Canadians and Europeans are competing groups in certain occupations, while they have complementary skills in others; and (3) immigrants from the Third World and the Canadians are slightly competing groups in certain occupations."     

A Network-Based Measure of the Socio-Economic Roots of the Migration Flows

Social Indicators Research - This paper provides a unified view for defining a measure of the reasons behind migration flows whose nature is of social and economic type. To this aim, worldwide...     

On some consistent tests of mutual independence among several random vectors of arbitrary dimensions

Statistics and Computing - Testing for mutual independence among several random vectors is a challenging problem, and in recent years, it has gained significant attention in statistics and machine...     

Development and evaluation of the physical activity questionnaire for elderly Japanese: the Nakanojo study

The Physical Activity Questionnaire for Elderly Japanese (PAQ-EJ) is a self-administered physical activity questionnaire for elderly Japanese; the authors report here on its repeatability and direct and indirect validity. Reliability was assessed by repeat administration after 1 month. Direct validation was based on accelerometer data collected every 4 s for 1 month in 147 individuals age 65-85 years. Indirect validation against a 10-item Barthel index (activities of daily living [ADL]) was completed in 3,084 individuals age 65-99 years. The test-retest coefficient was high (r = .64-.71). Total and subtotal scores for lower (transportation, housework, and labor) and higher intensity activities (exercise/sports) were significantly correlated with step counts and durations of physical activity <3 and >or=3 METs (r = .41, .28, .53), respectively. Controlling for age and ADL, scores for transportation, exercise/sports, and labor were greater in men, but women performed more housework. Sex- and ADL- or age-adjusted PAQ-EJ scores were significantly lower in older and dependent people. PAQ-EJ repeatability and validity seem comparable to those of instruments used in Western epidemiological studies.     

Natural Resource Management in Pastoral Africa

Current research on rangeland ecology suggests that we have less to fear from pastoral land stewardship than was previously thought. On the one hand, the natural environments exploited by pastoralists are generally robust and resilient. And on the other hand, pastoral techniques of land management are not as dysfunctional as was once widely assumed. While regulation of pastoral activity may be necessary in specific circumstances, there no longer exists a broad scientific mandate to control or modify almost every aspect of pastoral land use in order to preserve the environment.     

Effect of Health on Retirement of Older Americans: a Competing Risks Study

Retirement is an important event in the life of an individual. The decision to retire or exit from full-time employment may be motivated by several factors, including health. This paper explores the effect of both subjective and relatively more objective physical and mental health conditions on the probability of exit from full-time employment. Using longitudinal data on older Americans from ten waves of the Health and Retirement Study (1992–2010), eight health indices are created from a wide range of health measures by principal component analysis. The effect of these health indices on the time until exit from full-time employment is empirically examined in a proportional hazard model. Single and competing risk specifications are estimated that allow for multiple spells of full-time employment and control for unobserved heterogeneity. The main results suggest that better self-reported health decreases the likelihood of exit from full- time employment, while poor physical health (functional limitations factor) increases the likelihood of exit from full-time employment via complete retirement and disability. For mental health, I find that depression increases the likelihood of exit via complete retirement, part-time work and unemployment while cognitive disorders lead to an increase in likelihood of exit via the disability exit route. Hence, physical and mental health problems are both impediments to continued work. These results have implications for public policies targeted towards retaining older workers within the labor market.     

Classification rules for triply multivariate data with an AR(1) correlation structure on the repeated measures over time

In this article we study the problem of classification of three-level multivariate data, where multiple q$q$-variate observations are measured on u$u$-sites and over p$p$-time points, under the assumption of multivariate normality. The new classification rules with certain structured and unstructured mean vectors and covariance structures are very efficient in small sample scenario, when the number of observations is not adequate to estimate the unknown variance–covariance matrix. These classification rules successfully model the correlation structure on successive repeated measurements over time. Computation algorithms for maximum likelihood estimates of the unknown population parameters are presented. Simulation results show that the introduction of sites in the classification rules improves their performance over the existing classification rules without the sites.     

A likelihood based estimator for vector autoregressive processes

A onestep estimator, which is an approximation to the unconditional maximum likelihood estimator (MLE) of the coefficient matrices of a Gaussian vector autoregressive process is presented. The onestep estimator is easy to compute and can be computed using standard software. Unlike the computation of the unconditional MLE, the computation of the onestep estimator does not require any iterative optimization and the computation is numerically stable. In finite samples the onestep estimator generally has smaller mean square error than the ordinary least squares estimator. In a simple model, where the unconditional MLE can be computed, numerical investigation shows that the onestep estimator is slightly worse than the unconditional MLE in terms of mean square error but superior to the ordinary least squares estimator. The limiting distribution of the onestep estimator for processes with some unit roots is derived.