A Bayesian method for classification and discrimination

We discuss Bayesian analyses of traditional normal-mixture models for classification and discrimination. The development involves application of an iterative resampling approach to Monte Carlo inference, commonly called Gibbs sampling, and demonstrates routine application. We stress the benefits of exact analyses over traditional classification and discrimination techniques, including the ease with which such analyses may be performed in a quite general setting, with possibly several normal-mixture components having different covariance matrices, the computation of exact posterior classification probabilities for observed data and for future cases to be classified, and posterior distributions for these probabilities that allow for assessment of second-level uncertainties in classification.     

Low dose risk estimation via simultaneous statistical inferences

Summary.  The paper develops and studies simultaneous confidence bounds that are useful for making low dose inferences in quantitative risk analysis. Application is intended for risk assessment studies where human, animal or ecological data are used to set safe low dose levels of a toxic agent, but where study information is limited to high dose levels of the agent. Methods are derived for estimating simultaneous, one-sided, upper confidence limits on risk for end points measured on a continuous scale. From the simultaneous confidence bounds, lower confidence limits on the dose that is associated with a particular risk (often referred to as a bench-mark dose ) are calculated. An important feature of the simultaneous construction is that any inferences that are based on inverting the simultaneous confidence bounds apply automatically to inverse bounds on the bench-mark dose.     

Benchmark Analysis: Shopping with Proper Confidence

We discuss the issue of using benchmark doses for quantifying (excess) risk associated with exposure to environmental hazards. The paradigm of low-dose risk estimation in dose-response modeling is used as the primary application scenario. Emphasis is placed on making simultaneous inferences on benchmark doses when data are in the form of proportions, although the concepts translate easily to other forms of outcome data.     

Population structure and correlation between auxiliary and target variables may affect precision of estimates in forest inventory

Simulations of forest inventory in several populations compared simple random with “quick probability proportional to size” (QPPS) sampling. The latter may be applied in the absence of a list sampling frame and/or prior measurement of the auxiliary variable. The correlation between the auxiliary and target variables required to render QPPS sampling more efficient than simple random sampling varied over the range 0.3–0.6 and was lower when sampling from populations that were skewed to the right. Two possible analytical estimators of the standard error of the estimate of the mean for QPPS sampling were found to be less reliable than bootstrapping.     

NDIS Self‐Management Approaches: Opportunities for choice and control or an Uber‐style wild west?

This article examines the emerging challenges and opportunities presented by self‐management options in Australia's National Disability Insurance Scheme (NDIS). We examine the three different ways in which NDIS participants can opt to self‐manage their funding and services, including direct employment and emerging Uber‐style online platforms, and explore the potential implications of these options for NDIS participants, service providers and the disability support workforce. In particular, we focus on these options in relation to the transition to a marketised services landscape being developed alongside the NDIS, and examine both the risks and opportunities for each stakeholder group. Through this analysis, we identify implications for policy and practice, in particular around regulatory mechanisms and the role of government within this emerging market economy and transforming service landscape.     

Comparing the U.S. Decennial Census Coverage Estimates for Children from Demographic Analysis and Coverage Measurement Surveys

Following every U.S. decennial census since 1960, the U.S. Census Bureau has evaluated the completeness of coverage using two different methods. Demographic analysis (DA) compares the census counts to a set of independent population estimates to infer coverage differences by age, sex, and race. The survey-based approach (also called dual system estimation or DSE) provides coverage estimates based on matching data from a post-enumeration survey to census records. This paper reviews the fundamentals of the two methodological approaches and then initially examines the results of these two methods for the 2010 decennial census in terms of consistency and inconsistency for age groups. The authors find that the two methods produce relatively consistent results for all age groups, except for young children. Consequently, the paper focuses on the results for children. Results of the 1990, 2000, and 2010 decennial censuses are shown for the overall population in this age group and by demographic detail (age, race, and Hispanic origin). Among children, the DA and DSE results are most inconsistent for the population aged 0–4 and most consistent for ages 10–17. Results also show that DA and DSE are more consistent for Black than non-Black populations. The authors discuss possible explanations for the differences in the two methods for young children and conclude that the DSE approach may underestimate the net undercount of young children due to correlation bias.     

Jamaica,Three Years Later: Effects of Intensified Pro-Gay Activism on Severe Prejudice Against Lesbians and Gay Men

Jamaica has developed an international reputation for severe anti-gay prejudice. However, in the past few years, between 2012 and 2015, intensified waves of activism have increased the visibility of lesbian, gay, bisexual, and transgender (LGBT) Jamaicans, and supported their social and legal inclusion in Jamaican society. This research investigated the effects of that activism by taking advantage of two large, representative surveys of Jamaicans’ attitudes toward lesbians and gay men: one in 2012 and one in 2015. Over the three-year period there were significant reductions in desire for social distance and opposition to gay rights. However, there was no significant change in anti-gay attitudes, and there was evidence of an increase in anti-gay behaviors. There was also no evidence of polarization of responses to gay men and lesbians; rather, the most prejudiced Jamaicans showed the largest reductions in bias. Implications of these findings for activism in Jamaica and other anti-gay countries are discussed.