Vocational Psychology and Career Guidance Practice: An International Partnership

Vast changes in the world of work spurred by rapid technological growth and globalization have called for a more inclusive, progressive, and forward thinking conceptualization of vocational theory, practice, training, and policy. Discussions across 8 discussion groups at the 2007 joint symposium of the International Association for Educational and Vocational Guidance, Society for Vocational Psychology, and National Career Development Association addressed various topics in the field of vocational psychology and career guidance. Several themes emerged that have captured the attention of career scholars and practitioners across the globe: culture and context in theory and practice, research as a process within a contextual system, partnership and collaboration, and social responsibility and public policy.     

Lag Length Selection for Unit Root Tests in the Presence of Nonstationary Volatility

A number of recent papers have focused on the problem of testing for a unit root in the case where the driving shocks may be unconditionally heteroskedastic. These papers have, however, taken the lag length in the unit root test regression to be a deterministic function of the sample size, rather than data-determined, the latter being standard empirical practice. We investigate the finite sample impact of unconditional heteroskedasticity on conventional data-dependent lag selection methods in augmented Dickey–Fuller type regressions and propose new lag selection criteria which allow for unconditional heteroskedasticity. Standard lag selection methods are shown to have a tendency to over-fit the lag order under heteroskedasticity, resulting in significant power losses in the (wild bootstrap implementation of the) augmented Dickey–Fuller tests under the alternative. The proposed new lag selection criteria are shown to avoid this problem yet deliver unit root tests with almost identical finite sample properties as the corresponding tests based on conventional lag selection when the shocks are homoskedastic.     

Testing for heteroscedasticity occuring at unknown points

This paper considers procedures for the detection of heteroscedasticity when it occurs at unknown points. First the number of points is assumed known apriori and then this assumption is relaxed so that both the position and the number of possible aberrant observations is unknown. Monte Carlo evidence is provided on the performance of both tests and they are found to perform reasonably.     

Efficacy of Risk-Based, Culturally Sensitive Ogaa (Walleye) Consumption Advice for Anishinaabe Tribal Members in the Great Lakes Region

The Great Lakes Indian Fish and Wildlife Commission (GLIFWC) has produced Ogaa (walleye— Sander vitreus ) consumption advisories since 1996 for Anishinaabe from GLIFWC member tribes in the 1837 and 1842 ceded territories of Wisconsin. GLIFWC's advisory maps were revised in 2005 to address cultural sensitivities (to protect tribal lifeways), to utilize recent mercury exposure information, and to incorporate changes in advisory levels for methyl mercury. Lake-specific, risk-based, culturally sensitive consumption advice was provided on color-coded maps for two groups: children under age 15 years and females of childbearing age, and males 15 years and older and females beyond childbearing age. The maps were distributed to, and a behavioral intervention program developed for, the six GLIFWC member tribes in Wisconsin as well as member tribes in Minnesota and the 1842 ceded territory of Michigan. Tribal fish harvesters, tribal health care providers, women of childbearing age or with young children, tribal leaders, elders, and children were targeted specifically for the behavioral intervention. The efficacy of the behavioral intervention was assessed using surveys of 275 tribal fish harvesters from Wisconsin, 139 tribal harvesters from Michigan and Minnesota, and 156 Wisconsin women of childbearing age. Significant increases in the percentage of survey participants who indicated awareness of advisory maps occurred among Wisconsin harvesters (increase from 60% to 77%), Michigan and Minnesota harvesters (29% to 51%), and women of childbearing age in Wisconsin (40% to 87%). A significant increase in preference for smaller Ogaa occurred among tribal harvesters in Wisconsin (41% to 72%) and tribal harvesters in Michigan and Minnesota (49% to 71%), although not among women of childbearing age. The GLIFWC map-based advisory program did not adversely affect tribal harvest of Ogaa, which increased from 63,000 to 88,000 fish in the three states after the intervention.     

Asymptotic non-null distribution of a test of equality of exponential populations

In this paper further asymptotic expansions of the non-null distribution of the likelihood ratio criterion for testing the equality of several one parameter exponential distributions are obtained when the alternatives are close to the hypothesis. These expansions are obtained for the first time in terms of beta distributions.     

On evaluating interactive statistical program packages

Most statistical computing for data analysis has come to depend upon statistical program packages. In recent years, interactive computing has become widespread both on large time-sharing systems and on mini-computers. This paper identifies ways in which interactive statistical software packages differ from batchoriented software and discusses evaluation considerations pertaining specifically to interactive packages.     

Gibbs sampling for marginal posterior expectations

In earlier work (Gelfand and Smith, 1990 and Gelfand et al, 1990) a sampling based approach using the Gibbs sampler was offered as a means for developing marginal posterior densities for a wide range of Bayesian problems several of which were previously inaccessible. Our purpose here is two-fold. First we flesh out the implementation of this approach for calculation of arbitrary expectations of interest. Secondly we offer comparison with perhaps the most prominent approach for calculating posterior expectations, analytic approximation involving application of the LaPlace method. Several illustrative examples are discussed as well. Clear advantages for the sampling based approach emerge.     

Surveillance of the interaction parameter of the ising model

Surveillance to detect changes of spatial patterns is of interest in many areas such as environmental control and regional analysis. Here the interaction parameter of the Ising model, is considered. A minimal sufficient statistic and its asymptotic distribution are used. It is demonstrated that the convergence to normal, distribution is rapid. The main result is that when the lattice is large, all approximations are better in several respects. It is shown that, for large lattice sizes, earlier results on surveillance of a normally distributed random variable can be used in cases of most interest. The expected delay of alarm at a fixed level of false alarm probability is examined for some examples.     

A powerful test for uniformity to detect highly peaked alternativedensities

A new class of statistical tests for uniformity based on sample ranges is proposed to detect a uniform density contaminated by a density with one or more high peaks. These kinds of alternatives occur quite frequently, especially in physics. It is shown that the proposed tests arc consistent and have high Pitman asymptotic relative efficiencies. Results of a Monte Carlo power study indicate that they, compared with other tests of uniformity, possess good power properties.A comparative study of various tests is also conducted using real data. An effcient algorithm for computing out test statistic and a table of percentage points are given, providing a practical guide for using the new test.     

Comparing MCDA Aggregation Methods in Constructing Composite Indicators Using the Shannon-Spearman Measure

Composite indicators have been increasingly recognized as a useful tool for performance monitoring, benchmarking comparisons and public communication in a wide range of fields. The usefulness of a composite indicator depends heavily on the underlying data aggregation scheme where multiple criteria decision analysis (MCDA) is commonly used. A problem in this application is the determination of an appropriate MCDA aggregation method. Of the many criteria for comparing MCDA methods, the Shannon-Spearman measure (SSM) is one that compares alternative MCDA aggregation methods in constructing composite indicators based on the information loss concept. This paper assesses the effectiveness of the SSM using Monte Carlo approach-based uncertain analysis and variance-based sensitivity analysis techniques. It is found that most of the variation in the SSM arises from the uncertainty in choosing an aggregation method. Therefore, the SSM can be considered as an effective measure for comparing MCDA aggregation methods in constructing composite indicators. We also use the SSM to evaluate five MCDA aggregation methods in constructing composite indicators and present the findings.