House price indices

The new FT House Price Index aims to end the confusion that arises from the current plethora of indices. Simon Briscoe examines these various indices and explains the methodology behind the FT Index.     

Scholarly Communication 2.0: Exploring Researchers' Opinions on Web 2.0 for Scientific Knowledge Creation, Evaluation and Dissemination

This paper presents the results of a survey aimed at gauging the potential acceptance of a collaborative and Web 2.0 inspired scholarly communication sector. While this sector has seen the birth of a multitude of innovative initiatives, there is still little empirical evidence of the acceptance of such initiatives by researchers. We received 349 completed questionnaires from researchers of many different disciplines. The results of the survey show that there is a strong positive attitude towards Web 2.0 and open publishing approaches. However, the major challenge still resides in combining free dissemination of results with robust and reliable quality control mechanisms.     

Proposed best practice for statisticians in the reporting and publication of pharmaceutical industry‐sponsored clinical trials

In this paper we set out what we consider to be a set of best practices for statisticians in the reporting of pharmaceutical industry‐sponsored clinical trials. We make eight recommendations covering: author responsibilities and recognition; publication timing; conflicts of interest; freedom to act; full author access to data; trial registration and independent review. These recommendations are made in the context of the prominent role played by statisticians in the design, conduct, analysis and reporting of pharmaceutical sponsored trials and the perception of the reporting of these trials in the wider community. Copyright © 2010 John Wiley & Sons, Ltd.     

Bayesian kernel projections for classification of high dimensional data

A Bayesian multi-category kernel classification method is proposed. The algorithm performs the classification of the projections of the data to the principal axes of the feature space. The advantage of this approach is that the regression coefficients are identifiable and sparse, leading to large computational savings and improved classification performance. The degree of sparsity is regulated in a novel framework based on Bayesian decision theory. The Gibbs sampler is implemented to find the posterior distributions of the parameters, thus probability distributions of prediction can be obtained for new data points, which gives a more complete picture of classification. The algorithm is aimed at high dimensional data sets where the dimension of measurements exceeds the number of observations. The applications considered in this paper are microarray, image processing and near-infrared spectroscopy data.     

An alternate version of the conceptual predictive statistic based on a symmetrized discrepancy measure

The conceptual predictive statistic, C_p, is a widely used criterion for model selection in linear regression. C_p serves as an estimator of a discrepancy, a measure that reflects the disparity between the generating model and a fitted candidate model. This discrepancy, based on scaled squared error loss, is asymmetric: an alternate measure is obtained by reversing the roles of the two models in the definition of the measure. We propose a variant of the C_p statistic based on estimating a symmetrized version of the discrepancy targeted by C_p. We claim that the resulting criterion provides better protection against overfitting than C_p, since the symmetric discrepancy is more sensitive towards detecting overspecification than its asymmetric counterpart. We illustrate our claim by presenting simulation results. Finally, we demonstrate the practical utility of the new criterion by discussing a modeling application based on data collected in a cardiac rehabilitation program at University of Iowa Hospitals and Clinics.     

Women and crime the world over

This article examines female crime rates in twenty-seven countries over the past thirtyfive years. The results show that there has been an overall increase in total crime rates for all of the countries, and that the more economically advanced and industrialized countries have higher crime rates than the less developed nations. All countries also experienced an increase in the percent of all crimes committed by women. The percentages of violent crimes committed by women—specifically homicide and robbery—were consistently low across countries and increased only slightly over time. The percentages of property and financial crimes committed by women—specifically theft and fraud—were consistently higher than the percentages for violent crimes, and have increased more substantially over time. In addition, an analysis of the most recent data revealed a positive and significant relationship between women's overall crime rates and the countries' economic development. In those countries in which women occupy a higher status, as measured by formal years of schooling and representation in the labor force, we found some positive and significant correlations with the arrest rates for theft and fraud. There were also some strong negative relationships between female arrest rates for homicide and their status in society.     

Eminent Social Scientists’ Views on Immigration Issues: 1985 and 2006

Following up on a research note by Stephen Moore published in 1985, this article compares the results of the survey conducted in 1985 against one carried out in 2006 on the views of eminent social scientists (economists, political scientists, psychologists, sociologists, historians and anthropologists) on immigration issues. Specifically, the surveys report on whether the respondents are likely to favor an increase in the number of immigrants who are allowed into the United States and other issues such as whether immigrants improve the economy.

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Bayesian phylogenetic inference from animal mitochondrial genome arrangements

Summary. The determination of evolutionary relationships is a fundamental problem in evolutionary biology. Genome arrangement data are potentially more informative than deoxyribonucleic acid sequence data for inferring evolutionary relationships between distantly related taxa. We describe a Bayesian framework for phylogenetic inference from mitochondrial genome arrangement data using Markov chain Monte Carlo methods. We apply the method to assess evolutionary relationships between eight animal phyla.     

Changing times in pharmaceutical statistics: 2000‐2020

In a previous paper we considered how pharmaceutical statistics had changed between 1980 and 2000. In this paper we go on to consider some of the likely influences and changes in the world of pharmaceutical statistics over the next twenty years. Statistical research by pharmaceutical companies is supported, although its direct value in boosting company profits is challenged. The duality between fraud and conflict of interest is explored, particularly with regard to data and safety monitoring boards. Political correctness within clinical trials and (allegedly) better patient‐oriented outcomes is questioned and the whole notion of intention‐to‐treat and per‐protocol analyses is rejected in favour of pragmatic trials and explanatory trials. The dominance of SAS software within the industry is explored and the possibility for change considered. Finally, whilst the future of pharmaceutical companies is not addressed, the impact of future mergers, collaborations and take‐overs between clinical research organizations is considered. Copyright © 2002 John Wiley & Sons, Ltd.