Inference in Targeted Group‐Sequential Covariate‐Adjusted Randomized Clinical Trials

This article is devoted to the construction and asymptotic study of adaptive, group‐sequential, covariate‐adjusted randomized clinical trials analysed through the prism of the semiparametric methodology of targeted maximum likelihood estimation. We show how to build, as the data accrue group‐sequentially, a sampling design that targets a user‐supplied optimal covariate‐adjusted design. We also show how to carry out sound statistical inference based on such an adaptive sampling scheme (therefore extending some results known in the independent and identically distributed setting only so far), and how group‐sequential testing applies on top of it. The procedure is robust (i.e. consistent even if the working model is mis‐specified). A simulation study confirms the theoretical results and validates the conjecture that the procedure may also be efficient.     

The Role of Criminal Social Identity in the Relationship between Criminal Friends and Criminal Thinking Style within a Sample of Recidivistic Prisoners

Previous research suggests a direct relationship between criminal friends and criminal thinking style; however, social identity theory proposes that identity mediates the impact of social group members on development of thinking styles. This research project is the first attempt to empirically test the mediating role of criminal social identity in the development of criminal thinking styles within a recidivistic prison sample (N = 312). The structural equation model of criminal thinking style presented and tested in this study supports the central predictions of social identity theory, with findings demonstrating an indirect effect of antisocial friend associations on criminal thinking through in-group affect and in-group ties with criminal in-group members that reflect two of three dimensions of the measure of criminal social identity applied in the current study. Further implications in relation to theory and previous studies are discussed.     

Constructing an Accounting Journal Website

Abstract

To increase the effectiveness and efficiency of searches for information, accounting students, researchers, practitioners, and regulators could benefit from a Website devoted to the electronic access to journals. The site described here addresses such a need in the business discipline of accounting. On the site, the titles of over 470 journals are listed and categorized by topical areas within accounting. Then, within each accounting category, the journals are grouped according to their Internet accessibility. To provide the user with quick access to the various journals, the site provides links to the homepages of the various journals. Serials Review 2002; 28:201–205.     

Serials Spoken Here

Abstract

This article describes the concepts of Web 2.0 and Lib 2.0 and how they can be applied to libraries and in a library environment.     

The NISO Institutional Identifiers (I2) Working Group

Abstract

Recognizing the importance of the institution as a critical entity in any information model, from information creation to information sharing, NISO (National Information Standards Organization) has formed a working group to develop a standard (Z39.94) for identifying institutions. This installment of “Standards Update” will discuss the mission and objectives of that working group and provide some information about its timelines for developing the standard.     

CORE (Cost of Resource Exchange) Standard

Abstract

This article describes the CORE (Cost of Resource Exchange) standard. CORE defines an XML schema to allow the exchange of financial information relating to library resources among library systems.     

Smooth estimation of a monotone density

We investigate the interplay of smoothness and monotonicity assumptions when estimating a density from a sample of observations. The nonparametric maximum likelihood estimator of a decreasing density on the positive half line attains a rate of convergence of [Formula: See Text] at a fixed point t if the density has a negative derivative at t. The same rate is obtained by a kernel estimator of bandwidth [Formula: See Text], but the limit distributions are different. If the density is both differentiable at t and known to be monotone, then a third estimator is obtained by isotonization of a kernel estimator. We show that this again attains the rate of convergence [Formula: See Text], and compare the limit distributions of the three types of estimators. It is shown that both isotonization and smoothing lead to a more concentrated limit distribution and we study the dependence on the proportionality constant in the bandwidth. We also show that isotonization does not change the limit behaviour of a kernel estimator with a bandwidth larger than [Formula: See Text], in the case that the density is known to have more than one derivative.