Ecological Community Structure Analyses in the Formulation,Implementation, and Enforcement of Law and Policy

Most of what is currently known about ecosystems derives from two sources: comprehensive studies by classical ecologists and economically motivated studies by resource specialists. The former have traditionally concentrated on natural or long-undisturbed ecosystems, the latter on those few species in managed or polluted ecosystems that are harvested, hunted, or fished. A recent genre of legislation, drafted with insight provided by the scientific community, recognizes the dearth of ecological information on managed or polluted communities (which are becoming far more ubiquitous and important) and dramatically raises the requirements for comprehensive data and data analyses to guide managerial and pollution abatement policies. This paper describes several important current efforts to use ecological community structure analyses to implement and enforce such legislation and some effects of such analyses on environmental policy.     

Home run or strikeout: The dynamics of public opinion on new sports facilities

Determinants of political support for new sports facilities are explored. We test to what extent the civic attachment and civic optimism of a respondent promotes support for new facilities. Survey data from the 2005 CBS News/New York Times monthly poll were analyzed to find variables that affected public support for a new stadium for the New York Mets and a new arena for the New Jersey Nets. Whether New Yorkers’ were optimistic about the future of New York and whether they planned to continue living in New York had a significant impact on whether they supported new facilities. Demographic factors that frequently explain political differences did not have a significant effect. Respondents with greater civic attachment and optimism were more likely to support major sports projects. The findings open the door for additional research on how civic attachment and optimism impact the willingness of community residents to support major public projects.     

Uniform convergence of an empirical cdf based on a relatively small number of order statistics

An empirical distribution function F_m, defined on a subset of order statistics of a random sample of size n taken from the distribution of a random variable with continuous distribution function F, is shown to converge uniformly with probability one to F. Small sample distributions of the one and two sided deviations and the asymptotic normality of the standardized F_m are established. The relative efficiency of F_m as compared to the classical empirical distribution function is calculated and tabled. for n = 10, 20, 50, 100, 200.     

The Role of Beliefs in Sexual Behavior of Adolescents: Development and Validation of an Adolescent Sexual Expectancies Scale

This article reports on the development and psychometric properties of the Adolescent Sexual Expectancies Scale (ASEXS). Data were obtained from three annual longitudinal surveys of youth aged 10–17 at the first administration (N=932 at Wave 3). Confirmatory factor analyses indicated that 4 correlated factors corresponding to Social Risk, Social Benefit, Health Risk, and Pleasure adequately represented the expectancy items. High alpha coefficients and stability across survey waves indicated good internal and test–retest reliability for these factors. Latent variable autoregressive analyses indicated that Social Risk expectancies predicted changes in sexual behavior over the course of the study. Multigroup analyses established that the measurement and predictive models were equivalent for males and females and across age groups. The ASEXS provides researchers with a useful measure for examining adolescents' expectancy beliefs about the consequences of sexual behavior.     

Conditional Score Tests for Heteroscedasticity in the Two-Way Error Components Model

This paper extends the one-way heteroskedasticity score test of Holly and Gardiol (2000, In: Krishnakumar, J, Ronchetti, E (Eds.), Panel Data Econometrics: Future Directions, North-Holland, Amsterdam, pp. 199–211) to two conditional Lagrange Multiplier (LM) tests of heteroskedasticity under contiguous alternatives within the two-way error components model framework. In each case, the derivation of Rao's efficient score statistics for testing heteroskedasticity is first obtained. Then, based on a specific set of assumptions, the asymptotic distribution of the score under contiguous alternatives is established. Finally, the expression for the score test statistic in the presence of heteroskedasticity and related asymptotic local powers of these score test statistics are derived and discussed.     

Markov's Inequality and Chebyshev's Inequality for Tail Probabilities: A Sharper Image

Markov's inequality gives an upper bound on the probability that a nonnegative random variable takes large values. For example, if the random variable is the lifetime of a person or a machine, Markov's inequality says that the probability that an individual survives more than three times the average lifetime in the population of such individuals cannot exceed one-third. Here we give a simple, intuitive geometric interpretation and derivation of Markov's inequality. These results lead to inequalities sharper than Markov's when information about conditional expectations is available, as in reliability theory, demography, and actuarial mathematics. We use these results to sharpen Chebyshev's tail inequality also.     

Institutional Academic Industry Relationship: Results of Interviews with University Leaders

The purpose of this study was to explore qualitatively the nature, consequences and management of institutional academic industry relationships (IAIRs) in the life and health sciences. The results of our interviews suggest that in the institutions we visited IAIRs are common and deeply embedded in the academic enterprise both among institutional officials and the organization itself. Many believe these relationships have potential benefits for the research and education mission while creating the potential for conflicts of interest. Further tracking and study of IAIRs is required to understand and anticipate the full effects of these relationships on the scientific enterprise in the United States.     

Predicting probabilities for the 2010 FIFA World Cup games using a Poisson-Gamma model

In this paper, we provide probabilistic predictions for soccer games of the 2010 FIFA World Cup modelling the number of goals scored in a game by each team. We use a Poisson distribution for the number of goals for each team in a game, where the scoring rate is considered unknown. We use a Gamma distribution for the scoring rate and the Gamma parameters are chosen using historical data and difference among teams defined by a strength factor for each team. The strength factor is a measure of discrimination among the national teams obtained from their memberships to fuzzy clusters. The clusters are obtained with the use of the Fuzzy C-means algorithm applied to a vector of variables, most of them available on the official FIFA website. Static and dynamic models were used to predict the World Cup outcomes and the performance of our predictions was evaluated using two comparison methods.     

Institutional academic industry relationship: results of interviews with university leaders

The purpose of this study was to explore qualitatively the nature, consequences and management of institutional academic industry relationships (IAIRs) in the life and health sciences. The results of our interviews suggest that in the institutions we visited IAIRs are common and deeply embedded in the academic enterprise both among institutional officials and the organization itself. Many believe these relationships have potential benefits for the research and education mission while creating the potential for conflicts of interest. Further tracking and study of the IAIRs is required to understand and anticipate the full effects of these relationships on the scientific enterprise in the United States.