bluuebunny/crossref_metadata_2025_split huggingface dataset:
Menopause as a long‐term risk to health: implications of general practitioner accounts of prevention for women's choice and decision‐making
Authors: Murtagh Madeleine J. , Hepworth Julie 
Published: March 2003

AbstractOver the past two decades medical researchers and modernist feminist researchers have contested the meaning of menopause. In this article we examine various meanings of menopause in major medical and feminist literature and the construction of menopause in a semi‐structured interview study of general practitioners in rural South Australia. Three discursive themes are identified in these interviews; (i) the hormonal menopause – symptoms, risk, prevention; (ii) the informed menopausal woman; and (iii) decision‐making and hormone replacement therapy. By using the discourse of prevention, general practitioners construct menopause in relation to women's health care choices, empowerment and autonomy. We argue that the ways in which these concepts are deployed by general practitioners in this study produces and constrains the options available to women. The implications of these general practitioner accounts are discussed in relation to the proposition that medical and feminist descriptions of menopause posit alternative but equally‐fixed truths about menopause and their relationship with the range of responses available to women at menopause. Social and cultural explanations of disease causality (c.f.Germov 1998, Hardey 1998) are absent from the new menopause despite their being an integral part of the framework of the women's health movement and health promotion drawn on by these general practitioners. Further, the shift of responsibility for health to the individual woman reinforces practice claims to empower women, but oversimplifies power relations and constructs menopause as a site of self‐surveillance. The use of concepts from the women's health movement and health promotion have nevertheless created change in both the positioning of women as having ‘choices’ and the positioning of some general practitioners in terms of greater information provision to women and an attention to the woman's autonomy. In conclusion, we propose that a new menopause has evolved from a discursive shift in medicine and that there exists within this new configuration, claiming the empowerment of women as an integral part of health care for menopause, the possibility for change in medical practice which will broaden, strengthen, and maintain this position.
Stochastic labelling of biological images
Authors: Ayala G. , Simó A. 
Published: March 2003

Many hypotheses made by experimental researchers can be formulated as a stochastic labelling of a given image. Some stochastic labelling methods for random closed sets are proposed in this paper. Molchanov (I. Molchanov, 1984, Theor. Probability and Math. Statist.29, 113–119) provided the probabilistic background for this problem. However, there is a lack of specific labelling models. Ayala and Simó (G. Ayala and A. Simó, 1995, Advances in Applied Probability27, 293–305) proposed a method in which, given the whole set of connected components, every component is classified in a certain phase or category in a completely random way. Alternative methods are necessary in case the random labelling hypothesis is not reliable. A different kind of labelling method is proposed that considers the environment: the type of every connected component is a function of its location.Two different biphase images are studied: a cross section of a nerve from a rat, and a cross section of an optic nerve from a lizard.
Time‐series–cross‐section Data
Authors: Beck Nathaniel 
Published: March 2003

This article treats the analysis of ‘time‐series–cross‐section’ (TSCS) data. Such data consists of repeated observations on a series of fixed units. Examples of such data are annual observations on the political economy of OECD nations in the post‐war era. TSCS data is distinguished from ‘panel’ data, in that asymptotics are in the number of repeated observations, not the number of units.The article begins by treating the complications of TSCS data in an ‘old‐fashioned’ manner, that is, as a nuisance which causes estimation difficulties. It claims that TSCS data should be analyzed via ordinary least squares with ‘panel correct standard errors’ rather than generalized least squares methods. Dynamics should be modeled via a lagged dependent variable or, if appropriate, a single equation error correction model.The article then treats more modern issues, in particular, the modeling of spatial effects and heterogeneity. It also claims that heterogeneity should be assessed with ‘panel cross‐validation’ as well as more standard tests. The article concludes with a discussion of estimation in the presence of a binary dependent variable.
Drug Use and Drug Trafficking in Europe
Authors: Boekhout van Solinge Tim 
Published: March 2003

Illicit drugs form an important sector of the world economy. A recent report of the United Nations' International Narcotics Control Board (INCB) stated that many estimations have been made of the total revenue of the illicit drug industry, most ranging from $300 billion to $500 billion (INCB 1997). According to this UN report ‘a growing body of evidence’ suggests that the true figure lies around $400 billion. The report further states this turnover would be equivalent to approximately 8% of total international trade. In 1994 this figure would have been larger than the international trade in iron and steel, and motor vehicles, and about the same size as the total international trade in textiles. Of course, the important economic value of drugs can be largely attributed to the simple fact they are illegal.This article aims to give an overview of some general trends in drug use and drug trafficking in Europe. This overview will not discuss all illicit drugs in detail, but will focus on two drugs, cannabis and heroin. The reasons for this are as follows. Speaking about the use of illicit substances, cannabis is by and large the one that is most used in Europe. Heroin, on the other hand, is used by very few people – in drug use surveys the prevalence of heroin is usually among the lowest – but it is the drug that is most associated with marginalisation and drug addiction. This also explains why the use of this drug is more visible than the use of other drugs. The second reason for concentrating on cannabis and heroin is that the trade in these drugs is most interesting from a geopolitical point of view.
“Two Concepts of Liberty” Through African Eyes
Authors: Siame C. N. 
Published: March 2003

In “Two Concepts of Liberty” Berlin notes the protean nature of the word “freedom” and then systematically proceeds to narrow its range of meanings. In the process, Berlin eliminates much of what most people, in everyday communication, regard as freedom, believing that this is in the best interest of intellectual clarity. As he puts it:[N]othing is gained by a confusion of terms. To avoid glaring inequality or widespread misery I am ready to sacrifice some, or all, of my freedom: I may do so willingly and freely: but it is freedom that I am giving up for the sake of justice or equality or the love of my fellow men. I should be guilt‐stricken, and rightly so, if I were not, in some circumstances, ready to make this sacrifice. But a sacrifice is not an increase in what is being sacrificed, namely freedom, however great the moral need or the compensation for it. Everything is what it is: liberty is liberty, not equality or fairness or justice or culture, or human happiness or a quiet conscience. (Emphasis added).Berlin's other, perhaps overarching, aim is to show how inattention to the specificity of the meanings of concepts might have potentially dangerous political repercussions. He implicitly argues that the intellectuals who promoted the idea of positive freedom as opposed to that of negative freedom contributed to the emergence of totalitarianism and fascism in Europe.
Estimating the Risk of Reoffending by using Exponential Mixture Models
Authors: Copas J. B. , Heydari F. 
Published: March 2003

Summary
In deciding whether to release a prisoner on parole, the Parole Board is provided with a statistical score which estimates the chance that the prisoner will reoffend within the period of time that he or she would otherwise be in prison. This score is based on a survival analysis of data on a sample of releases from long-term prison sentences. To capture most reoffences which occur within 2 years of release, follow-up must continue for at least 3 years to allow for the delay between offence and conviction. We reanalyse the data by using a model which explicitly allows for this delay. The new analysis can be applied to data with a substantially shorter length of follow-up. This means that risk scores can be constructed from more up-to-date data and at less cost.
Models, Assumptions and Model Checking in Ecological Regressions
Authors: Gelman Andrew , Park David K. , Ansolabehere Stephen , Price Phillip N. , Minnite Lorraine C. 
Published: March 2003

Summary
Ecological regression is based on assumptions that are untestable from aggregate data. However, these assumptions seem more questionable in some applications than in others. There has been some research on implicit models of individual data underlying aggregate ecological regression modelling. We discuss ways in which these implicit models can be checked from aggregate data. We also explore the differences in applications of ecological regressions in two examples: estimating the effect of radon on lung cancer in the United States and estimating voting patterns for different ethnic groups in New York City.
The Transition from University to Work: A Multilevel Approach to the Analysis of the Time to Obtain the First Job
Authors: Biggeri L. , Bini M. , Grilli L. 
Published: March 2003

Summary
The aim of the paper is to characterize the factors that determine the transition from university to work as well as to evaluate the effectiveness of universities and course programmes with respect to the labour market outcomes of their graduates. The study is focused on the analysis of the time to obtain the first job, taking into account the graduates’ characteristics and the effects pertaining to course programmes and universities. For this a three-level discrete time survival model is used, where the logit of the hazard—conditionally on the random effects at course programme and university level—is a linear function of the covariates. The analysis is accomplished by using a large data set from a survey on job opportunities for the 1992 Italian graduates.
A Review and Discussion of Prospective Statistical Surveillance in Public Health
Authors: Sonesson Christian , Bock David 
Published: March 2003

SummaryA review of methods suggested in the literature for sequential detection of changes in public health surveillance data is presented. Many researchers have noted the need for prospective methods. In recent years there has been an increased interest in both the statistical and the epidemiological literature concerning this type of problem. However, most of the vast literature in public health monitoring deals with retrospective methods, especially spatial methods. Evaluations with respect to the statistical properties of interest for prospective surveillance are rare. The special aspects of prospective statistical surveillance and different ways of evaluating such methods are described. Attention is given to methods that include only the time domain as well as methods for detection where observations have a spatial structure. In the case of surveillance of a change in a Poisson process the likelihood ratio method and the Shiryaev–Roberts method are derived.
Patterns and Trends in Occupational Attainment Of First Jobs in the Netherlands, 1930–1995: Ordinary Least Squares RegressionversusConditional Multinomial Logistic Regression
Authors: Dessens Jos A. G. , Jansen Wim , Ganzeboom Harry B. G. , Van Der Heijden Peter G. M. 
Published: March 2003

SummaryThis paper brings together the virtues of linear regression models for status attainment models formulated by second-generation social mobility researchers and the strengths of log-linear models formulated by third-generation researchers, into fourth-generation social mobility models, by using conditional multinomial logistic regression (CMLR). These CMLR models are capable of capturing the discrete and multidimensional nature of social mobility patterns (a characteristic of third-generation output) while reducing the number of parameters leading to parsimonious models (a characteristic of second-generation output). Using data from eight pooled surveys in the Netherlands, an extended Blau–Duncan status attainment model is formulated and analysed. The corresponding CMLR model is formulated incorporating general and specific inheritance effects. The final CMLR model gives a relatively parsimonious description of Dutch mobility patterns, similar to the extended Blau–Duncan model, at the same time offering the possibility of including specific effects where necessary. Effects of gender and education appear to be too complex to be captured by a single parameter.
Parameter Orthogonality in Mixed Regression Models for Survival Data
Authors: Hutton J. L. , Solomon P. J. 
Published: March 2003

Summary
The implications of parameter orthogonality for the robustness of survival regression models are considered. The question of which of the proportional hazards or the accelerated life families of models would be more appropriate for analysis is usually ignored, and the proportional hazards family is applied, particularly in medicine, for convenience. Accelerated life models have conventionally been used in reliability applications. We propose a one-parameter family mixture survival model which includes both the accelerated life and the proportional hazards models. By orthogonalizing relative to the mixture parameter, we can show that, for small effects of the covariates, the regression parameters under the alternative families agree to within a constant. This recovers a known misspecification result. We use notions of parameter orthogonality to explore robustness to other types of misspecification including misspecified base-line hazards. The results hold in the presence of censoring. We also study the important question of when proportionality matters.
Transformations for Smooth Regression Models with Multiplicative Errors
Authors: Eagleson G. K. , Müller H. G. 
Published: March 2003

Summary
We consider whether one should transform to estimate nonparametrically a regression curve sampled from data with a constant coefficient of variation, i.e. with multiplicative errors. Kernel-based smoothing methods are used to provide curve estimates from the data both in the original units and after transformation. Comparisons are based on the mean-squared error (MSE) or mean integrated squared error (MISE), calculated in the original units. Even when the data are generated by the simplest multiplicative error model, the asymptotically optimal MSE (or MISE) is surprisingly not always obtained by smoothing transformed data, but in many cases by directly smoothing the original data. Which method is optimal depends on both the regression curve and the distribution of the errors. Data-based procedures which could be useful in choosing between transforming and not transforming a particular data set are discussed. The results are illustrated on simulated and real data.
On an Alternative Solution to the Vector Spline Problem
Authors: Yee Thomas W. 
Published: March 2003

Summary
Yee and Wild have presented additive extensions to multivariate regression models including generalized estimating equations. The back-bone of their methods was a vector spline, which was solved by direct solution. A back-fitting solution to the vector spline problem is presented here, with the implication that existing generalized additive model software can, with moderate effort, be modified to implement multivariate models.
A Class of Local Likelihood Methods and Near-Parametric Asymptotics
Authors: Eguchi Shinto , Copas John 
Published: March 2003

Summary
The local maximum likelihood estimate θ^ t of a parameter in a statistical model f(x, θ) is defined by maximizing a weighted version of the likelihood function which gives more weight to observations in the neighbourhood of t. The paper studies the sense in which f(t, θ^t) is closer to the true distribution g(t) than the usual estimate f(t, θ^) is. Asymptotic results are presented for the case in which the model misspecification becomes vanishingly small as the sample size tends to ∞. In this setting, the relative entropy risk of the local method is better than that of maximum likelihood. The form of optimum weights for the local likelihood is obtained and illustrated for the normal distribution.
Estimating the Variance In Nonparametric Regression—What is a Reasonable Choice?
Authors: Dette Holger , Munk Axel , Wagner Thorsten 
Published: March 2003

Summary
The exact mean-squared error (MSE) of estimators of the variance in nonparametric regression based on quadratic forms is investigated. In particular, two classes of estimators are compared: Hall, Kay and Titterington's optimal difference-based estimators and a class of ordinary difference-based estimators which generalize methods proposed by Rice and Gasser, Sroka and Jennen-Steinmetz. For small sample sizes the MSE of the first estimator is essentially increased by the magnitude of the integrated first two squared derivatives of the regression function. It is shown that in many situations ordinary difference-based estimators are more appropriate for estimating the variance, because they control the bias much better and hence have a much better overall performance. It is also demonstrated that Rice's estimator does not always behave well. Data-driven guidelines are given to select the estimator with the smallest MSE.
Parametric Regression Models for Continuous Time Removal and Recapture Studies
Authors: Lin D. Y. , Yip P. S. F. 
Published: March 2003

Summary
We use a class of parametric counting process regression models that are commonly employed in the analysis of failure time data to formulate the subject-specific capture probabilities for removal and recapture studies conducted in continuous time. We estimate the regression parameters by modifying the conventional likelihood score function for left-truncated and right-censored data to accommodate an unknown population size and missing covariates on uncaptured subjects, and we subsequently estimate the population size by a martingale-based estimating function. The resultant estimators for the regression parameters and population size are consistent and asymptotically normal under appropriate regularity conditions. We assess the small sample properties of the proposed estimators through Monte Carlo simulation and we present an application to a bird banding exercise.
Asymptotic Inference for Mixture Models by Using Data-Dependent Priors
Authors: Wasserman Larry 
Published: March 2003

Summary
For certain mixture models, improper priors are undesirable because they yield improper posteriors. However, proper priors may be undesirable because they require subjective input. We propose the use of specially chosen data-dependent priors. We show that, in some cases, data-dependent priors are the only priors that produce intervals with second-order correct frequentist coverage. The resulting posterior also has another interpretation: it is the product of a fixed prior and a pseudolikelihood.
Conditional Statistical Inference and Quantification of Relevance
Authors: Sundberg Rolf 
Published: March 2003

SummaryWe argue that it can be fruitful to take a predictive view on notions such as the precision of a point estimator and the confidence of an interval estimator in frequentist inference. This predictive approach has implications for conditional inference, because it immediately allows a quantification of the concept of relevance for conditional inference. Conditioning on an ancillary statistic makes inference more relevant in this sense, provided that the ancillary is a precision index. Not all ancillary statistics satisfy this demand. We discuss the problem of choice between alternative ancillary statistics. The approach also has implications for the best choice of variance estimator, taking account of correlations with the squared error of estimation itself. The theory is illustrated by numerous examples, many of which are classical.
Some Aspects of the Design and Analysis of Cluster Randomization Trials
Authors: Donner Allan 
Published: March 2003

SUMMARY
Trials which randomize intact social groups, or clusters, to different interventions are becoming increasingly widespread. Although statistically less efficient than trials which randomize individuals, such designs are often preferred from a practical or ethical point of view, particularly in the evaluation of health care or educational strategies. We discuss selected issues that arise in the conduct of such trials, including the choice of design, ethical implications, sample size estimation and approaches to the analysis. The discussion is closely tied to methodological issues that have arisen in a recent evaluation trial of a new antenatal care programme, as sponsored by the Special Programme of Research, Development and Research Training in Human Reproduction of the World Health Organization.
Bayesian Graphical Modelling: A Case-Study in Monitoring Health Outcomes
Authors: Spiegelhalter David J. 
Published: March 2003

SUMMARY
Bayesian graphical modelling represents the synthesis of several recent developments in applied complex modelling. After describing a moderately challenging real example, we show how graphical models and Markov chain Monte Carlo methods naturally provide a direct path between model specification and the computational means of making inferences on that model. These ideas are illustrated with a range of modelling issues related to our example. An appendix discusses the BUGS software.
Parametric Relative Survival Regression Using Generalized Linear Models with Application to Hodgkin’s Lymphoma
Authors: Weller Edie A. , Feuer Eric J. , Frey Carolin M. , Wesley Margaret N. 
Published: March 2003

SUMMARY
Changes in survival rates during 1940–1992 for patients with Hodgkin’s disease are studied by using population-based data. The aim of the analysis is to identify when the breakthrough in clinical trials of chemotherapy treatments started to increase population survival rates, and to find how long it took for the increase to level off, indicating that the full population effect of the breakthrough had been realized. A Weibull relative survival model is used because the model parameters are easily interpretable when assessing the effect of advances in clinical trials. However, the methods apply to any relative survival model that falls within the generalized linear models framework. The model is fitted by using modifications of existing software (SAS, GLIM) and profile likelihood methods. The results are similar to those from a cause-specific analysis of the data by Feuer and co-workers. Survival started to improve around the time that a major chemotherapy breakthrough (nitrogen mustard, Oncovin, prednisone and procarbazine) was publicized in the mid 1960s but did not level off for 11 years. For the analysis of data where the cause of death is obtained from death certificates, the relative survival approach has the advantage of providing the necessary adjustment for expected mortality from causes other than the disease without requiring information on the causes of death.