Predictive Bayesian Microbial Dose-Response Assessment Based on Suggested Self-Organization in Primary Illness Response: Cryptosporidium parvum

The probability of illness caused by very low doses of pathogens cannot generally be tested due to the numbers of subjects that would be needed, though such assessments of illness dose response are needed to evaluate drinking water standards. A predictive Bayesian dose-response assessment method was proposed previously to assess the unconditional probability of illness from available information and avoid the inconsistencies of confidence-based approaches. However, the method uses knowledge of the conditional dose-response form, and this form is not well established for the illness endpoint. A conditional parametric dose-response function for gastroenteric illness is proposed here based on simple numerical models of self-organized host-pathogen systems and probabilistic arguments. In the models, illnesses terminate when the host evolves by processes of natural selection to a self-organized critical value of wellness. A generalized beta-Poisson illness dose-response form emerges for the population as a whole. Use of this form is demonstrated in a predictive Bayesian dose-response assessment for cryptosporidiosis. Results suggest that a maximum allowable dose of 5.0 x 10(-7) oocysts/exposure (e.g., 2.5 x 10(-7) oocysts/L water) would correspond with the original goals of the U.S. Environmental Protection Agency Surface Water Treatment Rule, considering only primary illnesses resulting from Poisson-distributed pathogen counts. This estimate should be revised to account for non-Poisson distributions of Cryptosporidium parvum in drinking water and total response, considering secondary illness propagation in the population.     

Statistical consulting

The paper and the special issue focus on the activity of statistical consulting and its varieties. This includes academic consulting, consulting to and in industry as well as statistics in public media.     

A Bayesian Hierarchical Model for the Evaluation of a Website

Consider a website and the surfers visiting its pages. A typical issue of interest, for example while monitoring an advertising campaign, concerns whether a specific page has been designed successfully, i.e. is able to attract surfers or address them to other pages within the site. We assume that the surfing behaviour is fully described by the transition probabilities from one page to another, so that a clickstream (sequence of consecutively visited pages) can be viewed as a finite-state-space Markov chain. We then implement a variety of hierarchical prior distributions on the multivariate logits of the transition probabilities and define, for each page, a content effect and a link effect. The former measures the attractiveness of the page due to its contents, while the latter signals its ability to suggest further interesting links within the site. Moreover, we define an additional effect, representing overall page success, which incorporates both effects previously described. Using WinBUGS, we provide estimates and credible intervals for each of the above effects and rank pages accordingly.     

African Americans and municipal employment: A test of two perspectives

A survey of the extant literature addressing the factors that drive African American municipal employment offers two broad types of explanations: (1) Black political power and (2) institutional. A comparative assessment of the performance of each of these explanations fills a gap in the literature by illuminating the differences of these distinct perspectives when it comes to employment of Blacks in the public sector. Focusing on six Florida cities from 1960 to 2000, this study tests the predictive power of each of these explanations comparatively for four city departments. The findings indicate that the Black political power explanation performs better than the institutional explanation as a predictor of Black employment.     

Glass ceilings or sticky floors? A model of high-income law graduates

Minorities and females are underrepresented in the top-income quintile of law school graduates. Employing a binary logistic regression model, I examine whether this is due to a“glass ceiling” (an invisible barrier erected by third parties) or a“sticky floor” (self-imposed limitations regarding employment). My major finding is that being female, a minority, or disabled did not significantly reduce one's probability of making the top-income quintile once hours of work, experience, and other factors are taken into account. My findings directly contradict the large body of glass-ceiling literature and support the sticky-floor model. I thank the Law School Admission Council for funding this research. Helpful comments and suggestions were received from Robert Nelson of Northwestern University and the American Bar Foundation, Steven Conroy of the University of West Florida, and R. Kim Craft and Douglas Bonzo of Southern Utah University. The views expressed here are solely those of the author and do not necessarily reflect those of the institutions or persons listed above.     

CORPORATE TAX INCIDENCE AND INEFFICIENCY WHEN CORPORATE AND NONCORPORATE GOODS ARE CLOSE SUBSTITUTES

An important deficiency in Harberger's [1962] model of corporate income taxation is its inability to consider both corporate and noncorporate production of the same good. Within-industry substitution has potentially major implications for both the excess burden and incidence of the corporate tax.
We analyze this within-industry substitution using a model in which each industry/sector contains corporate and noncorporate firms (with identical production functions) which produce goods that are close substitutes. The scope for considerable within-industry substitution of noncorporate for corporate capital leads to a very much larger excess burden than that in the Harberger model.     

Detecting parameter shift in garch models

This paper applies recent theories of testing for parameter constancy to the conditional variance in a GARCH model. The supremum Lagrange multiplier test for conditional Gaussian GARCH models and its robustified variants are discussed. The asymptotic null distribution of the test statistics are derived from the weak convergence of the scores, and the critical values from the hitting probability of squared Bessel process.

Monte Carlo studies on the finite sample size and power performance of the supremum LM tests are conducted. Applications of these tests to S&P 500 indicate that the hypothesis of stable conditional variance parameters can be rejected.     

Adoptive parents to children with severe developmental disabilities: A profile

A sample of 16 women and men who accompanied their adopted children with severe developmental disabilities to a medical appointment at Henry Ford Hospital's Multidisciplinary Care Clinic during the one-year period beginning July 1, 1988 are described in the context of their parental role vis-a-vis these children. Results of the study are presented through use of a six-part organizational scheme: demographic and social traits of the parents and their adopted children, the adopted children in family context, life satisfactions of the parents, adoption motives, adoption satisfactions, and humanization of the children.     

log-logistic survival estimation based on failure-censored data

Approximations of the Bayesian estimators of the survival function based on the censored data of the log-logistic distribution are obtained under squared-error and log-odds squared-error loss functions. A numerical example is presented. Through a Monte Carlo simulation study, the behavior of the approximations found by Tierney & Kadane and Lindley are compared with a method suggested by Weiss & Howlader.