Book reviews

Theory and Society -     

A New Test for Short Memory in Long Memory Time Series

This article considers short memory characteristics in a long memory process. We derive new asymptotic results for the sample autocorrelation difference ratios. We used these results to develop a new portmanteau test that determines if short memory parameters are statistically significant. In simulations, the new test can detect short memory components more often than the Ljung-Box test when these short memory components are in fact within a long memory process. Interestingly, our test finds short memory autocorrelations in U.S. inflation rate data, whereas the Ljung-Box test fails to find these autocorrelations. Modeling these short memory autocorrelations of the inflation rate data leads to improved model accuracy and more precise prediction.     

Who cares about consent requirements for sourcing human embryonic stem cells? Are errors in the past really errors of the past?

Through an Access to Information Act request, we have obtained the consent forms used by the providers of every human embryonic stem cell (hESC) line approved for use by the Canadian Institutes of Health Research (CIHR), and examined them to verify whether or not they meet the consent requirements established by Canadian law and regulations. Our findings show that at least seven out of ten consent forms studied did not satisfy these minimum requirements. We then outline various options for responding to this situation in terms of: (i) remedial measures for dealing with executive problems with regulatory oversight procedures; and (ii) remedial measures for dealing with the impugned lines.     

Partnerships, Power and the "New" Politics of Community Participation in British Health Care

Multi–sectoral approaches to health improvement in its broadest sense have entailed an emphasis by the British government upon partnership working in and around community involvement in planning processes. New service planning and delivery organizations in the health service—primary care groups and primary care trusts—thus have to ensure that public and patient involvement strategies reflect a coordinated, if not integrated, multi–sectoral approach to such involvement. But how are these enforced partnership arrangements shaping the approach taken by primary care groups and trusts to the issue of public and patient involvement? More particularly, is the traditional dominance of health service managers and the medical profession in decision–making processes under challenge? This article draws on a study of primary care groups and trusts in three districts in order to gauge perceptions and calculations with regard to partnerships for involvement. Results appear to suggest that health service managers and practitioners continue to exercise considerable influence in comparison to that of patients and citizens. But, if the findings are viewed in the broader contexts of government managerialist strategies of surveillance and accountability and the growth of service–user and advocacy organizations, partnerships may offer significant scope for “lay” challenges to managerial and medical power.     

Health Policy and the Politics of Evidence

National decisions on the drugs, treatments and medical devices that should be funded through public expenditure are a fundamental element of health policy. But despite a political emphasis upon evidence‐based policy, the results of rigorous clinical trials and statistical modelling techniques rarely speak for themselves. So, does the pre‐eminence traditionally accorded to quantitative data in the medical field underpin policy decisions on a consistent basis? Or are more subtle, less transparent characteristics of context and interaction evident in the shaping of attendant decisions? This article considers these questions by drawing on a study of decision‐making in the National Institute for Health and Clinical Excellence (NICE)—an organization established by the British government in 1999 to decide whether selected health technologies should be made available throughout the National Health Service in England and Wales. In broad terms, the findings point to the primacy of arguments based on quantitatively oriented, experimentally derived data but also to a discursive hegemony of clinicians and health economists in mediating, including or debarring more qualitative, experientially based evidence. A more complex, dynamic understanding of policy governance in the field of health technology appraisal—founded on a discursive appropriation of the idea of the “common good”—goes some way to explaining the persistence of this hegemony despite an avowedly inclusive, plural approach to decision‐making.     

Product partition latent variable model for multiple change-point detection in multivariate data

The product partition model (PPM) is a well-established efficient statistical method for detecting multiple change points in time-evolving univariate data. In this article, we refine the PPM for the purpose of detecting multiple change points in correlated multivariate time-evolving data. Our model detects distributional changes in both the mean and covariance structures of multivariate Gaussian data by exploiting a smaller dimensional representation of correlated multiple time series. The utility of the proposed method is demonstrated through experiments on simulated and real datasets.     

A semi-parametric approach to robust parameter design

Parameter design or robust parameter design (RPD) is an engineering methodology intended as a cost-effective approach for improving the quality of products and processes. The goal of parameter design is to choose the levels of the control variables that optimize a defined quality characteristic. An essential component of RPD involves the assumption of well estimated models for the process mean and variance. Traditionally, the modeling of the mean and variance has been done parametrically. It is often the case, particularly when modeling the variance, that nonparametric techniques are more appropriate due to the nature of the curvature in the underlying function. Most response surface experiments involve sparse data. In sparse data situations with unusual curvature in the underlying function, nonparametric techniques often result in estimates with problematic variation whereas their parametric counterparts may result in estimates with problematic bias. We propose the use of semi-parametric modeling within the robust design setting, combining parametric and nonparametric functions to improve the quality of both mean and variance model estimation. The proposed method will be illustrated with an example and simulations.     

Armed robbery and the meanings of money

In this study, we investigate the meanings active armed robbers give to money before, during, and after their crimes and how these meanings shape their offending. We do so by examining interviews undertaken from 1994 to 1995 with robbers in St. Louis, Missouri, USA. Prior to their robberies, the interviewees' desperation leads them to define money as essential to survival. Immediately following robberies and in looking back on them, they come to view this essential money in other ways as well—as too time-consuming to get, as “easy,” or as guilt-free. These meanings facilitate the contradictory way robbers see money as “fast” after offences. We discuss how these shifting meanings of money shape and are shaped by robbers' structural positions, cultural outlooks, and social relations. In doing so, we also help to explain how the shifting meanings of money play into criminogenic cycles of predatory offending.