Longitudinal dynamic analyses of cognition in the health and retirement study panel

The purpose of this paper is to highlight some classic issues in the measurement of change and to show how contemporary solutions can be used to deal with some of these issues. Five classic issues will be raised here: (1) Separating individual changes from group differences; (2) options for incomplete longitudinal data over time, (3) options for nonlinear changes over time; (4) measurement invariance in studies of changes over time; and (5) new opportunities for modeling dynamic changes. For each issue we will describe the problem, and then review some contemporary solutions to these problems base on Structural Equation Models (SEM). We will fit these SEM to using existing panel data from the Health & Retirement Study (HRS) cognitive variables. This is not intended as an overly technical treatment, so only a few basic equations are presented, examples will be displayed graphically, and more complete references to the contemporary solutions will be given throughout.     

Moments of Inertia and Graph Separators

Graphs that arise from the finite element or finite difference methods often include geometric information such as the coordinates of the nodes of the graph. The geometric separator algorithm of Miller, Teng, Thurston, and Vavasis uses some of the available geometric information to find small node separators of graphs. The algorithm utilizes a random sampling technique based on the uniform distribution to find a good separator. We show that sampling from an elliptic distribution based on the inertia matrix of the graph can significantly improve the quality of the separator. More generally, given a cost function f on the unit d-sphere Ud, we can define an elliptic distribution based on the second moments of f. The expectation of f with respect to the elliptic distribution is less than or equal to the expectation with respect to the uniform distribution, with equality only in degenerate cases. We also demonstrate experimentally that the benefit gained by the use of the additional geometric information is significant. Some previous algorithms have used the moments of inertia heuristically, and suffer from extremely poor worst case performance. This is the first result, to our knowledge, that incorporates the moments of inertia into a provably good strategy.     

Hospital-sponsored networks. The rush to consolidate and the future of medical practice

As the medical delivery system undergoes fundamental change, there is a growing pressure on hospitals to form networks with physicians. The prime motivation for these entities is to preserve market share and fill beds. There is likewise intense pressure on physicians to join them, even if these networks do not serve their best interests, or the goal of fostering physician-centered practice. A transformation is under way, however, that may well place doctors again in the central role of guiding the new modes of medical practice in the United States.     

Meet the mandate to measure clinical quality

The mandate for health care organizations to be accountable for quality, as well as price, is now unavoidable. The Joint Commission's ORYX project is requiring every hospital to measure clinical outcomes of a majority of its patients within the next three years. This mandate can be met best with systems of clinical outcomes measurement that provide valid, reliable risk adjustment; yield meaningful information about many different diseases and procedures; and measure more than mortality or cost--all using primarily billing data. New outcomes measurement tools with all of these capabilities are available and have already enabled quality improvement in dozens of hospitals across the U.S.     

Industry and the environment: a case study of cleaner technologies in selected European countries

The aim of this case study is to discuss the role of technology in addressing environmental problems. The paper tries to scratch beneath the surface of the increasingly frequent ‘quick-fix’ solutions to the present environmental problems, based on such beguiling catchwords as Cleaner Technologies, Best Available Technologies, and Best Available Technologies Not Exceeding Excessive Costs, etc., in an attempt to discover whether there is any substance in them, or whether they are just full of hot air. Recent data from case studies performed by the author in Germany and Finland as well as a postal questionnaire in Denmark are presented. The paper analyses and discusses the roles and responsibilities of designers, industrialists, and government policy-makers. It is argued that existing regulatory regimes, supranational industrial structures, and market mechanisms do not favour the development of cleaner technologies, nor do they promote a reduction in consumption patterns. Evidence from ongoing empirical research in Northwest Europe suggests that industry is far from developing and/or implementing cleaner technologies. The paper closes with a discussion of some of the policy implications involved and some examples of urgently needed further research.     

Problems of Growth in a High Technology Firm: Moving between Conscious and Unconscious Accounts of Organizational Processes

This paper explores an infrequently discussed methodological divide within qualitative research; that between conscious and unconscious accounts of organizational processes. The paper makes use of an empirical case study of problems encountered in the growth of a high-technology company. The conscious accounts of growth treat members of the firm as knowledgeable agents whose understandings are then drawn upon to generate an account of growth in terms of interrelated processes of power, meaning and legitimacy. These conscious accounts are then complemented through an exploration of unconscious dynamics in the personality of the entrepreneur, the work group and the `family' structure of the firm. It is argued that the key shift in moving between conscious and unconscious interpretation, involves the bracketing of the reality claims implicit in conscious rationalizations, and a re-listening to research material as a largely unconscious projection of individuals' `inner worlds'. With unconscious interpretations, the character of language, its emotional content and in particular the sources of individual and group anxiety all realize a central importance. Despite the established divide in the literature between these two forms of interpretation, it is argued that the case suggests the value and necessity of their integration, particularly for the understanding of creativity.     

Liquid Chromatography Mass Spectrometry-Based Proteomics: Biological and Technological Aspects

Mass spectrometry-based proteomics has become the tool of choice for identifying and quantifying the proteome of an organism. Though recent years have seen a tremendous improvement in instrument performance and the computational tools used, significant challenges remain, and there are many opportunities for statisticians to make important contributions. In the most widely used "bottom-up" approach to proteomics, complex mixtures of proteins are first subjected to enzymatic cleavage, the resulting peptide products are separated based on chemical or physical properties and analyzed using a mass spectrometer. The two fundamental challenges in the analysis of bottom-up MS-based proteomics are: (1) Identifying the proteins that are present in a sample, and (2) Quantifying the abundance levels of the identified proteins. Both of these challenges require knowledge of the biological and technological context that gives rise to observed data, as well as the application of sound statistical principles for estimation and inference. We present an overview of bottom-up proteomics and outline the key statistical issues that arise in protein identification and quantification.     

Bayesian and likelihood-based inference for the bivariate normal correlation coefficient

The paper develops some objective priors for correlation coefficient of the bivariate normal distribution. The criterion used is the asymptotic matching of coverage probabilities of Bayesian credible intervals with the corresponding frequentist coverage probabilities. The paper uses various matching criteria, namely, quantile matching, highest posterior density matching, and matching via inversion of test statistics. Each matching criterion leads to a different prior for the parameter of interest. We evaluate their performance by comparing credible intervals through simulation studies. In addition, inference through several likelihood-based methods have been discussed.     

A frailty model for (interval) censored family survival data,applied to the age at onset of non-physical problems

Family survival data can be used to estimate the degree of genetic and environmental contributions to the age at onset of a disease or of a specific event in life. The data can be modeled with a correlated frailty model in which the frailty variable accounts for the degree of kinship within the family. The heritability (degree of heredity) of the age at a specific event in life (or the onset of a disease) is usually defined as the proportion of variance of the survival age that is associated with genetic effects. If the survival age is (interval) censored, heritability as usually defined cannot be estimated. Instead, it is defined as the proportion of variance of the frailty associated with genetic effects. In this paper we describe a correlated frailty model to estimate the heritability and the degree of environmental effects on the age at which individuals contact a social worker for the first time and to test whether there is a difference between the survival functions of this age for twins and non-twins.