Combining an Internal Pilot with an Interim Analysis for Single Degree of Freedom Tests

An internal pilot with interim analysis (IPIA) design combines interim power analysis (an internal pilot) with interim data analysis (two stage group sequential). We provide IPIA methods for single df hypotheses within the Gaussian general linear model, including one and two group t tests. The design allows early stopping for efficacy and futility while also re-estimating sample size based on an interim variance estimate. Study planning in small samples requires the exact and computable forms reported here. The formulation gives fast and accurate calculations of power, type I error rate, and expected sample size.     

Expansions for log densities of asymptotically normal estimates

Edgeworth–type expansions are given for the log density and also for the derivatives of the density of an asymptotically normal random variable having the standard expansions for its cumulants. Expansions for the log density are much simpler than for the density. In fact the rth term of the expansion for the log density is a polynomial of degree only r + 2, while that for the density is a polynomial of degree 3r.     

A “Reverse Order” Elementary Statistics Course

A family of coefficients for measuring monotone association is presented. These include measures of association of ordinal or interval variables such as gamma of Goodman and Kruskal, Somers's d_yx , Kendall's tau, or Spearman's rho as special cases. The article shows how a large number of measures of association can be put into a single general form. These coefficients are used as a basis for defining a variety of data analysis techniques.     

Use of weighted least squares regression jn simulation studies

When a simulation or Monte Carlo analysis uses the same set of N samples as input for the comparison of the power of tests, the resulting estimates of power are highly correlated. As a result, the statistical analysis of these results should use weighted least squares or other equivalent procedures. A reanalysis of one simulation study (Thode et al., 1983) found that the weighted least squares estimates had much smaller standard errors than the ordinary least squares estimates. The reduction in the standard errors of the parameters was a factor between 4 and 9 for the tests found to be more powerful. The necessary calculations are described.     

Classification Rules under Autoregressive and General Circulant Covariance

We develop classification rules for data that have an autoregressive circulant covariance structure under the assumption of multivariate normality. We also develop classification rules assuming a general circulant covariance structure. The new classification rules are efficient in reducing the misclassification error rates when the number of observations is not large enough to estimate the unknown variance–covariance matrix. The proposed classification rules are demonstrated by simulation study for their validity and illustrated by a real data analysis for their use. Analyses of both simulated data and real data show the effectiveness of our new classification rules.     

Neoliberalism and the reform of regulation policy in the Australian trucking sector: policy innovation or a repeat of known pitfalls?

This study explores the influences of neoliberalism on the design and operation of regulation policy in the Australian trucking sector. It examines the introduction of a programme of voluntary self-regulation and considers why despite known weaknesses, regulators persist with such policy reforms. The study draws on qualitative research involving representatives of policy and regulatory agencies as well as industry participants. The analysis examines the role of markets in directing truck operator interest towards public policy compliance objectives. This generates a diversity of responses from firms ranging from willing compliance to deceptive ritualism. The findings reveal how voluntary self-regulation appeals to some segments of industry and how in this case it also signals a shift in regulatory culture, facilitating a new and more engaging dialogue between industry and regulators around compliance and safety concerns. This study shows that advances in industry-regulator engagement help explain why neoliberal policy influences are often readily embraced by regulatory agencies. Here, we see how programmes of voluntary self-regulation present both symbolic and substantive value for key policy actors.     

Optimal Pricing and Rebate Strategies in a Two‐Level Supply Chain

For many product categories, manufacturers and retailers often offer rebates to stimulate sales. Due to certain adverse effects, however, some manufacturers and retailers are contemplating the elimination of their rebate programs. This paper sheds light on the debate about the value of rebate programs by presenting a model for evaluating the conditions under which a firm should offer rebates in a competitive environment. Specifically, we consider a two‐level supply chain comprising one manufacturer and one retailer. Each firm makes three decisions: the regular (wholesale or retail) price, whether or not to offer rebates, and the rebate value should the firm decide to launch a rebate program. We determine the equilibrium of a vertical competition game between the manufacturer (leader) and the retailer (follower), and we provide insights about how competition affects the conditions under which a firm should offer rebates in equilibrium.