Accuracy,confidence and consensus in bayesian hypothesis inference

Interest centres on a group of statisticians , each supplied with the same n sample datapoint sandmaking formal Bayesian inference with a common likelihood function but differing prior knowledge and utility functions.

Definitions are proposed which quantify, in a commensurable way, the inference processes of “accuracy”, “confidence” and “consensus” for the case of hypothesis inference with a fixed sample size n.

The general significance of comparing the three quantifiers is considered. As n increases the asymptotic behaviour of the quantifiers is evaluated and it is found that the three rates of convergence are of the same order as a function of n. The results are interpreted and some of their implications are discussed.     

Bootstrapping in least absolute value regression: an application to hypothesis testing

A Monte Carlo simulation is used to study the performance of hypothesis tests for regression coefficients when least absolute value regression methods are used. In small samples, the results of the simulation suggest that using the bootstrap method to compute standard errors will provide improved test performance     

More Powerful Tests from Confidence Interval p Values

In this article the problem of comparing two independent binomial populations is considered. It is shown that the test based on the confidence interval p value of Berger and Boos often is uniformly more powerful than the standard unconditional test. This test also requires less computational time.     

Correlation,Regression Lines,and Moments of Inertia

The R language, a freely available environment for statistical computing and graphics is widely used in many fields. This “expert-friendly” system has a powerful command language and programming environment, combined with an active user community. We discuss how R is ideal as a platform to support experimentation in mathematical statistics, both at the undergraduate and graduate levels. Using a series of case studies and activities, we describe how R can be used in a mathematical statistics course as a toolbox for experimentation. Examples include the calculation of a running average, maximization of a nonlinear function, resampling of a statistic, simple Bayesian modeling, sampling from multivariate normal, and estimation of power. These activities, often requiring only a few dozen lines of code, offer students the opportunity to explore statistical concepts and experiment. In addition, they provide an introduction to the framework and idioms available in this rich environment.     

How discrimination in adoptive,foster, and medical systems harms LGBTQ+ families: Research on the experiences of prospective parents

Abstract

LGBTQ+?people face multiple challenges to parenthood because of barriers such as discriminatory legislation and policies influencing foster parenting, adoption, and reproductive health services. This study documents these obstacles and examines their impact through a grounded theory analysis of interviews of LGBTQ+?prospective parents. Stressors included social isolation, unnecessary medicalization, prohibitive financial costs related to accessing social and medical services (sometimes across state lines), and being denied services, parental leave, and insurance coverage. Findings indicate that heteronormative attitudes and discrimination can lead to debilitating and enduring harm upon the economic, emotional, and relational well-being of growing LGBTQ+?families.     

ANTITRUST ECONOMICS AND CONSUMER PROTECTION ECONOMICS IN POLICY AND LITIGATION: WHY THE DISPARITY?

The lag in the use of microeconomics in consumer protection policy and litigation—as compared with the use of microeconomics in antitrust/competition policy and litigation—has at least three causes: a considerably shorter period of intellectual development; the specific historical origins and culture of the U.S. Federal Trade Commission (FTC), where this disparity is especially noticeable; and the splintering of consumer protection responsibilities across a very large number of federal and state agencies. This paper will expand on these themes and discuss their implications—including the opportunities for expanded research in the area of consumer protection economics. (JEL B12, B13, B21, D18, L41)     

Indicator development as a site of collective imagination? The case of European Commission policies on the circular economy

ABSTRACT

In recent years the concept of the circular economy gained prominence in EU policy-making. The circular economy promotes a future in which linear ‘make-use-dispose’ cultures are replaced by more circular models. In this paper, we use the concept of sociotechnical imaginaries to ask how an imaginary of circularity has been assembled and stabilized, which imaginative resources were drawn on, and how goals, priorities, benefits and risks haven been merged with discourses of innovation, sustainability and growth. Drawing on policy documents and interviews with policy officers of the European Commission, we argue that the monitoring framework and indicator development function as a site collective imagination in which desirable ‘circular’ futures are co-produced. These futures are imagined to provide novel opportunities for the private sector and to generate jobs and economic growth while at the same time improving the natural environment as measured by selected environmental indicators.