bluuebunny/crossref_metadata_2025 huggingface dataset:
Siblings bridging literacies in multilingual contexts
Authors: Williams Ann , Gregory Eve
Published: March 2003

It is a common assumption that economically disadvantaged and ethnic‐minority families are unlikely to share similar educational aims, beliefs and values to those of teachers. Such families are assumed to participate in very different home literacy practices from those of the school and children’s early reading difficulties have been attributed to such cultural differences. However, such dissonance is not always found. This paper explores the reciprocity of beliefs and literacy practices between two schools and their respective communities in London’s East End. The literacy practices, both in school and out of school, of Bangladeshi British and Anglo‐British primary school children were monitored and play activities between siblings recorded and analysed. The results showed older siblings reflecting the values of both community and school as they blended practices from each domain in their play with their younger brothers and sisters.
The Development of the UK National Lottery: 1992–96
Authors: Moore Peter G.
Published: March 2003

This paper outlines the build-up of the National Lottery launch, from the government 1992 white paper, the subsequent Parliamentary procedures leading to the National Lottery Act, the choice of Camelot as the operator in May 1994 and the nationwide launch of the lottery in November 1994. The paper outlines the achievements of the lottery and some longer-term issues that it faces.
Gender and Income Inequality in the UK 1968–90: The Feminization of Earnings or of Poverty?
Authors: Davies Hugh , Joshi Heather
Published: March 2003

This paper uses data from the Family Expenditure Survey for five selected years between 1968 and 1990 to examine trends in the income distribution in the UK, highlighting the role of women’s labour force participation and earnings. The increased labour force participation of married women (especially mothers of young children in the 1980s) made a greater contribution to the decline of the ‘traditional’ male breadwinner family than the increased number of lone parents. The lower half of the distribution of weekly earnings became increasingly dominated by women. Though women’s weekly earnings remained low relative to men’s, the increase in their participation meant that, over the period, an increased share of family income came from women’s labour market income: in 1990 nearly a quarter of the income of families with children came from women’s earnings. Women’s earnings were an important factor in keeping families out of poverty. There was no trend towards increasing feminization of poverty over the sample period. Adult women were somewhat more likely to be poor than adult men were, but female-headed families were very much more likely to be in poverty, and much more dependent on state benefits, than male-headed families were. Women’s increased role in the labour market affected those in male-headed families more than those in female-headed families. Alongside a broad tendency for women’s earnings to reduce poverty and inequality, there is evidence that the female population has become more economically polarized.
Acquired Immune Deficiency Syndrome Projections in England and Wales: Interplay of Methodology and Data
Authors: De Angelis D. , Day N. E. , Gill O. N.
Published: March 2003

Since the late 1980s, regular monitoring of the human immunodeficiency virus epidemic in England and Wales has been carried out through the work of successive national working groups. One of their tasks has been to provide short-term projections of the incidence of acquired immune deficiency syndrome. In this paper the data and methods used in this projection work are reviewed and results critically assessed with the aim of highlighting the strong interaction between methodological developments and data acquisition.
Measures of Mortality in the Study of Individuals Infected with the Human Immunodeficiency Virus in the UK Haemophilia Population
Authors: Darby S. C. , Ewart D. W.
Published: March 2003

Two statistical issues that have arisen in the course of a study of mortality and disease related to the human immunodeficiency virus (HIV) in the haemophilia population of the UK are discussed. The first of these concerns methods of standardization for age and it is shown that, when the mortality of HIV-infected individuals with different severities of haemophilia are compared, an analysis based on the ratio of observed to national expected deaths suggests that mortality in HIV-infected individuals depends on the severity of their haemophilia. This conclusion is inappropriate and mortality in HIV-infected individuals is, in fact, similar regardless of severity of haemophilia. The second part of the paper discusses the effect of using various end points for studies of survival and progression of HIV-related disease. In the present example it was possible to calculate relative survival in HIV-infected individuals, i.e. survival after correcting for mortality expected in the absence of HIV infection. An analysis based on absolute survival gave a very similar picture of the effect of age at infection to an analysis based on relative survival, whereas an analysis based on the time to diagnosis of acquired immune deficiency syndrome (AIDS) underestimated the effect substantially and the possible alternative end point of time to AIDS or HIV-related death was shown to be subject to considerable misclassification error.
Issues in the Design and Analysis of Therapeutic Trials in Human Immunodeficiency Virus Infection
Authors: Babiker A. , Darbyshire J. , Peto T. , Walker S.
Published: March 2003

The first randomized trial of antiviral therapy in human immunodeficiency virus (HIV) disease included 282 patients with acquired immune deficiency syndrome (AIDS) or AIDS-related complex and was stopped in 1986 after an average follow-up of 4 months because of a substantial reduction in mortality in the group who received zidovudine (AZT). The era of anti-HIV treatment had begun. This paper discusses some of the difficulties which have emerged over the subsequent 10 years as new anti-HIV drugs have been developed requiring evaluation in clinical trials. The trials in which the British Medical Research Council has played a major role (the Concorde, Alpha and Delta trials) and some of the key trials conducted by the AIDS Clinical Trials Group (ACTG) (the ACTG 019 and ACTG 175 trials) and the Community Programs for Clinical Research on AIDS (CPCRA) (the CPCRA 007 trial) in the US will be used to illustrate some of the issues faced by clinical trialists and governmental regulatory agencies in the evaluation of therapies for a disease which, in spite of advances in therapy, still has a high mortality.
Epidemiology and Litigation—The Sellafield Childhood Leukaemia Cases
Authors: Wakeford R.
Published: March 2003

Statisticians and scientists are often required to provide information outside the scientific community. One important example is as an expert witness in the law courts. The civil litigation cases of Reay versus British Nuclear Fuels plc and Hope versus British Nuclear Fuels plc are a vivid illustration of how science and scientists interact with the law and lawyers. The personal injury cases were decided on the basis of how a specific epidemiological association should be properly interpreted, and this involved many experts. It is desirable that statisticians and scientists understand the nature of expert evidence, and these two cases are used to illuminate the role of the scientist in civil litigation.
Dealing with Non-Ignorable Non-Response by Using an ‘Enthusiasm-to-Respond’ Variable
Authors: Copas A. J. , Farewell V. T.
Published: March 2003

In the National Survey of Sexual Attitudes and Lifestyles (NATSSAL), it is recognized that non-response is unlikely to be ignorable. In some surveys, in addition to the response variables of interest, there may also be an ‘enthusiasm-to-respond’ variable which is expected to be related to the probabilities of item and unit response. Inference techniques to deal with non-ignorable non-response, based on a propensity-to-respond score, can be developed when there are both item and unit non-responders. For the NATSSAL data, an interviewer-measured interviewee embarrassment variable is combined with demographics to produce a score for the propensity to respond. The necessary likelihood development is outlined and alternative approaches to interval estimation are compared. The methodology is illustrated through an estimation of virginity from NATSSAL data.
Forecasting on British Election Night 1997
Authors: Brown P. J. , Firth D. , Payne C. D.
Published: March 2003

An account is given of methods used to predict the outcome of the 1997 general election from early declared results, for use by the British Broadcasting Corporation (BBC) in its election night television and radio coverage. Particular features of the 1997 election include extensive changes to constituency boundaries, simultaneous local elections in many districts and strong tactical voting. A new technique is developed, designed to eliminate systematic sources of bias such as differential refusal, for incorporating prior information from the BBC’s exit poll. The sequence of forecasts generated on election night is displayed, with commentary.
A Multilevel Analysis of Longitudinal Ordinal Data: Evaluation of the Level of Physical Performance of Women Receiving Adjuvant Therapy for Breast Cancer
Authors: Ribaudo Heather J. , Bacchi M. , Bernhard J. , Thompson S. G.
Published: March 2003

Longitudinal health-related quality-of-life (QOL) data are often collected as part of clinical studies. Here two analyses of QOL data from a prospective study of breast cancer patients evaluate how physical performance is related to factors such as age, menopausal status and type of adjuvant treatment. The first analysis uses summary statistic methods. The same questions are then addressed using a multilevel model. Because of the structure of the physical performance response, regression models for the analysis of ordinal data are used. The analyses of base-line and follow-up QOL data at four time points over two years from 257 women show that reported base-line physical performance was consistently associated with later performance and that women who had received chemotherapy in the month before the QOL assessment had a greater physical performance burden. There is a slight power gain of the multilevel model over the summary statistic analysis. The multilevel model also allows relationships with time-dependent covariates to be included, highlighting treatment-related factors affecting physical performance that could not be considered within the summary statistic analysis. Checking of the multilevel model assumptions is exemplified.
Classical Multilevel and Bayesian Approaches to Population Size Estimation Using Multiple Lists
Authors: Fienberg S. E. , Johnson M. S. , Junker Brain W.
Published: March 2003

One of the major objections to the standard multiple-recapture approach to population estimation is the assumption of homogeneity of individual ‘capture’ probabilities. Modelling individual capture heterogeneity is complicated by the fact that it shows up as a restricted form of interaction among lists in the contingency table cross-classifying list memberships for all individuals. Traditional log-linear modelling approaches to capture–recapture problems are well suited to modelling interactions among lists but ignore the special dependence structure that individual heterogeneity induces. A random-effects approach, based on the Rasch model from educational testing and introduced in this context by Darroch and co-workers and Agresti, provides one way to introduce the dependence resulting from heterogeneity into the log-linear model; however, previous efforts to combine the Rasch-like heterogeneity terms additively with the usual log-linear interaction terms suggest that a more flexible approach is required. In this paper we consider both classical multilevel approaches and fully Bayesian hierarchical approaches to modelling individual heterogeneity and list interactions. Our framework encompasses both the traditional log-linear approach and various elements from the full Rasch model. We compare these approaches on two examples, the first arising from an epidemiological study of a population of diabetics in Italy, and the second a study intended to assess the ‘size’ of the World Wide Web. We also explore extensions allowing for interactions between the Rasch and log-linear portions of the models in both the classical and the Bayesian contexts.
Prospective Time Periodic Geographical Disease Surveillance Using a Scan Statistic
Authors: Kulldorff Martin
Published: March 2003

Most disease registries are updated at least yearly. If a geographically localized health hazard suddenly occurs, we would like to have a surveillance system in place that can pick up a new geographical disease cluster as quickly as possible, irrespective of its location and size. At the same time, we want to minimize the number of false alarms. By using a space–time scan statistic, we propose and illustrate a system for regular time periodic disease surveillance to detect any currently ‘active’ geographical clusters of disease and which tests the statistical significance of such clusters adjusting for the multitude of possible geographical locations and sizes, time intervals and time periodic analyses. The method is illustrated on thyroid cancer among men in New Mexico 1973–1992.
Dropping Out of University: A Statistical Analysis of the Probability of Withdrawal for UK University Students
Authors: Smith Jeremy P. , Naylor Robin A.
Published: March 2003

From individual level data for an entire cohort of undergraduate students in the ‘old’ universities in the UK, we use a binomial probit model to estimate the probability that an individual will ‘drop out’ of university before the completion of their degree course. We examine the cohort of students enrolling full time for a 3- or 4-year degree in the academic year 1989–1990. We find evidence to support both the hypothesis that the completion of courses by students is influenced by the extent of prior academic preparedness and the hypothesis that social integration at university is important. We also find an influence of unemployment in the county of prior residence, especially for poorer male students. Finally, we draw conclusions regarding the public policy of constructing university performance indicators in this area.
Estimating Reference Ranges from Stratified Two-stage Samples
Authors: Thompson Mary Lou , Edland Steven D. , Gibbons Laura E. , McCurry Susan M.
Published: March 2003

We present methodology for estimating age-specific reference ranges by using data from two-stage samples. On the basis of the information obtained in the first stage, the initial sample is stratified and random subsamples are drawn from each stratum, where the selection probabilities in this second-stage sampling may be different across strata in the population. The variable for which the reference ranges are to be established is measured at the second phase. The approach involves maximum likelihood estimation of the parameters of the age-specific distributions and separate estimation of the population stratum probabilities. These are combined to yield estimates of the quantiles of interest. The issue of variance estimation for the estimated quantiles is also addressed. The methodology is applied to the estimation of reference ranges for a cognitive test score in a study of non-demented older Japanese-Americans.
Analysis of Incomplete Durations with Application to Contraceptive Use
Authors: Ali Mohamed M. , Marshall Tom , Babiker Abdel G.
Published: March 2003

Models for analysing incomplete durations obtained from cross-sectional surveys are presented. The aim of the paper is to develop a framework for analysing the incomplete duration of episodes in progress at the time of the survey by formulating generalized linear models and fitting and assessing them by using standard statistical packages. The maximum quasi-likelihood method is used for model fitting. The choice of the distribution and the diagnostic procedures are discussed. Simulated data from two distributions (the Weibull and log-logistic distributions) are used to evaluate the methodology developed and to assess model misspecifications. A data set on the current use of the contraceptive pill from a cross-sectional survey in Egypt is analysed.
New Methods for Comparing Literacy Across Populations: Insights from the Measurement of Poverty
Authors: Denny Kevin
Published: March 2003

This paper analyses levels of low literacy across 12 countries by using the International Adult Literacy Survey. We go beyond existing work that only looks at the proportions below certain critical levels of literacy. Using methods developed for the measurement of poverty we calculate measures of literacy that are sensitive to the distribution of literacy within those defined as illiterate. This reveals a different pattern of the extent of literacy problems across countries and within some populations. These measures should be useful to policy makers who need to allocate resources to alleviate low literacy and numeracy.
Ehrenberg Law-Like Relationship and Anthropometry
Authors: Forcheh N.
Published: March 2003

Ehrenberg presented the simple law-like relationship log(w) = 0.8h + 0.4 ± 0.04 between the weight and height of children aged 5–13 years. Several researchers have confirmed that this relationship holds, irrespective of the child's ethnic, racial, gender and social class. In anthropometry, a weight–height relationship is used to measure the nutritional status of children. For this purpose, the World Health Organization have adopted the National Center for Health Statistics population as the international reference population. The relationship between the World Health Organization–National Center for Health Statistics anthropometric standards and Ehrenberg law-like relationship is examined. Differences between the weight-for-height relationship in anthropometry and the law-like relationship between weight and height for children are small and can be attributable to functional differences. It is found that an Ehrenberg law-like relationship can be extended to include children who are under 5 years old. Criteria for using the law-like relationship to assess the nutritional status of these children are thus suggested. The criteria are evaluated using anthropometric data of a sample of 513 children from a rural district of Botswana. The results indicate that the proposed method of using the law-like relationship to assess nutritional status is much simpler and at least as reliable as the existing methods in anthropometry.
Ignorability, Sufficiency and Ancillarity
Authors: Heitjan Daniel F.
Published: March 2003

This paper explores the relationship between ignorability, sufficiency and ancillarity in the coarse data model of Heitjan and Rubin. Bayes or likelihood ignorability has a natural relationship to sufficiency, and frequentist ignorability an analogous relationship to ancillarity. Weaker conditions, termed observed likelihood sufficiency, observed specific sufficiency and observed ancillarity, expand the concepts to models where the coarsening mechanism is sometimes, but not always, ignorable.
Parameter Neutral Optimum Design for Non-linear Models
Authors: Firth D. , Hinde J. P.
Published: March 2003

Some Bayesian approaches to D-optimum design of experiments are considered from the viewpoint of invariance under reparameterization of the underlying statistical model. An invariant criterion is proposed which does not require the detailed specification of a prior, and which is shown to be equivalent to G-optimality under a Jeffreys prior. The methods are applied and discussed in the contexts of exponential decay and quantal response models.
Wavelet Thresholding via A Bayesian Approach
Authors: Abramovich F. , Sapatinas T. , Silverman B. W.
Published: March 2003

We discuss a Bayesian formalism which gives rise to a type of wavelet threshold estimation in nonparametric regression. A prior distribution is imposed on the wavelet coefficients of the unknown response function, designed to capture the sparseness of wavelet expansion that is common to most applications. For the prior specified, the posterior median yields a thresholding procedure. Our prior model for the underlying function can be adjusted to give functions falling in any specific Besov space. We establish a relationship between the hyperparameters of the prior model and the parameters of those Besov spaces within which realizations from the prior will fall. Such a relationship gives insight into the meaning of the Besov space parameters. Moreover, the relationship established makes it possible in principle to incorporate prior knowledge about the function's regularity properties into the prior model for its wavelet coefficients. However, prior knowledge about a function's regularity properties might be difficult to elicit; with this in mind, we propose a standard choice of prior hyperparameters that works well in our examples. Several simulated examples are used to illustrate our method, and comparisons are made with other thresholding methods. We also present an application to a data set that was collected in an anaesthesiological study.
Understanding Exponential Smoothing Via Kernel Regression
Authors: Gijbels I. , Pope A. , Wand M. P.
Published: March 2003

Exponential smoothing is the most common model-free means of forecasting a future realization of a time series. It requires the specification of a smoothing factor which is usually chosen from the data to minimize the average squared residual of previous one-step-ahead forecasts. In this paper we show that exponential smoothing can be put into a nonparametric regression framework and gain some interesting insights into its performance through this interpretation. We also use theoretical developments from the kernel regression field to derive, for the first time, asymptotic properties of exponential smoothing forecasters.
Exponential Family State Space Models Based on a Conjugate Latent Process
Authors: Vidoni Paolo
Published: March 2003

This paper introduces non-linear and non-Gaussian state space models with analytic updating recursions for filtering and prediction. This new class of models involves some well-known results in the theory of exponential models and of exponential dispersion models and the latent process is defined in such a way that both the filtering and the prediction distributions turn out to be conjugate to the observation distribution at each step. The corresponding analytic and inferential properties are investigated and some simple examples are presented.
The Effect of Monte Carlo Approximation on Coverage Error of Double-Bootstrap Confidence Intervals
Authors: Lee S. M. S. , Young G. A.
Published: March 2003

A double-bootstrap confidence interval must usually be approximated by a Monte Carlo simulation, consisting of two nested levels of bootstrap sampling. We provide an analysis of the coverage accuracy of the interval which takes account of both the inherent bootstrap and Monte Carlo errors. The analysis shows that, by a suitable choice of the number of resamples drawn at the inner level of bootstrap sampling, we can reduce the order of coverage error. We consider also the effects of performing a finite Monte Carlo simulation on the mean length and variability of length of two-sided intervals. An adaptive procedure is presented for the choice of the number of inner level resamples. The effectiveness of the procedure is illustrated through a small simulation study.
Invariance and Factorial Models
Authors: McCullagh Peter
Published: March 2003

Two factors having the same set of levels are said to be homologous. This paper aims to extend the domain of factorial models to designs that include homologous factors. In doing so, it is necessary first to identify the characteristic property of those vector spaces that constitute the standard factorial models. We argue here that essentially every interesting statistical model specified by a vector space is necessarily a representation of some algebraic category. Logical consistency of the sort associated with the standard marginality conditions is guaranteed by category representations, but not by group representations. Marginality is thus interpreted as invariance under selection of factor levels (I-representations), and invariance under replication of levels (S-representations). For designs in which each factor occurs once, the representations of the product category coincide with the standard factorial models. For designs that include homologous factors, the set of S-representations is a subset of the I-representations. It is shown that symmetry and quasi-symmetry are representations in both senses, but that not all representations include the constant functions (intercept). The beginnings of an extended algebra for constructing general I-representations is described and illustrated by a diallel cross design.
On Variable Bandwidth Selection in Local Polynomial Regression
Authors: Doksum Kjell , Peterson Derick , Samarov Alex
Published: March 2003

The performances of data-driven bandwidth selection procedures in local polynomial regression are investigated by using asymptotic methods and simulation. The bandwidth selection procedures considered are based on minimizing ‘prelimit’ approximations to the (conditional) mean-squared error (MSE) when the MSE is considered as a function of the bandwidth h. We first consider approximations to the MSE that are based on Taylor expansions around h=0 of the bias part of the MSE. These approximations lead to estimators of the MSE that are accurate only for small bandwidths h. We also consider a bias estimator which instead of using small h approximations to bias naïvely estimates bias as the difference of two local polynomial estimators of different order and we show that this estimator performs well only for moderate to large h. We next define a hybrid bias estimator which equals the Taylor-expansion-based estimator for small h and the difference estimator for moderate to large h. We find that the MSE estimator based on this hybrid bias estimator leads to a bandwidth selection procedure with good asymptotic and, for our Monte Carlo examples, finite sample properties.
Parameterization and Inference for Nonparametric Regression Problems
Authors: Jiang Wenxin , Kipnis Victor , Midthune Douglas , Carroll Raymond J.
Published: March 2003

We consider local likelihood or local estimating equations, in which a multivariate function Θ(·) is estimated but a derived function λ(·) of Θ(·) is of interest. In many applications, when most naturally formulated the derived function is a non-linear function of Θ(·). In trying to understand whether the derived non-linear function is constant or linear, a problem arises with this approach: when the function is actually constant or linear, the expectation of the function estimate need not be constant or linear, at least to second order. In such circumstances, the simplest standard methods in nonparametric regression for testing whether a function is constant or linear cannot be applied. We develop a simple general solution which is applicable to nonparametric regression, varying-coefficient models, nonparametric generalized linear models, etc. We show that, in local linear kernel regression, inference about the derived function λ(·) is facilitated without a loss of power by reparameterization so that λ(·) is itself a component of Θ(·). Our approach is in contrast with the standard practice of choosing Θ(·) for convenience and allowing λ(·)> to be a non-linear function of Θ(·). The methods are applied to an important data set in nutritional epidemiology.
Conjugacy Class Prior Distributions on Metric-Based Ranking Models
Authors: Gupta Jayanti , Damien Paul
Published: March 2003

A new class of prior distributions for metric-based models in the analysis of fully and partially ranked data is developed. This class is attractive because it provides a meaningful way to encapsulate prior information about the parameters of the model. Three examples illustrate the ideas developed in the paper.
Influence Diagnostics and Outlier Tests for Semiparametric Mixed Models
Authors: Fung Wing-Kam , Zhu Zhong-Yi , Wei Bo-Cheng , He Xuming
Published: March 2003

Semiparametric mixed models are useful in biometric and econometric applications, especially for longitudinal data. Maximum penalized likelihood estimators (MPLEs) have been shown to work well by Zhang and co-workers for both linear coefficients and nonparametric functions. This paper considers the role of influence diagnostics in the MPLE by extending the case deletion and subject deletion analysis of linear models to accommodate the inclusion of a nonparametric component. We focus on influence measures for the fixed effects and provide formulae that are analogous to those for simpler models and readily computable with the MPLE algorithm. We also establish an equivalence between the case or subject deletion model and a mean shift outlier model from which we derive tests for outliers. The influence diagnostics proposed are illustrated through a longitudinal hormone study on progesterone and a simulated example.
Bandwidth Selection for Local Linear Regression Smoothers
Authors: Hengartner Nicolas W. , Wegkamp Marten H. , Matzner-Løber Eric
Published: March 2003

The paper presents a general strategy for selecting the bandwidth of nonparametric regression estimators and specializes it to local linear regression smoothers. The procedure requires the sample to be divided into a training sample and a testing sample. Using the training sample we first compute a family of regression smoothers indexed by their bandwidths. Next we select the bandwidth by minimizing the empirical quadratic prediction error on the testing sample. The resulting bandwidth satisfies a finite sample oracle inequality which holds for all bounded regression functions. This permits asymptotically optimal estimation for nearly any regression function. The practical performance of the method is illustrated by a simulation study which shows good finite sample behaviour of our method compared with other bandwidth selection procedures.
The Evaluation of General Non-Centred Orthant Probabilities
Authors: Miwa Tetsuhisa , Hayter A. J. , Kuriki Satoshi
Published: March 2003

The evaluation of the cumulative distribution function of a multivariate normal distribution is considered. The multivariate normal distribution can have any positive definite correlation matrix and any mean vector. The approach taken has two stages. In the first stage, it is shown how non-centred orthoscheme probabilities can be evaluated by using a recursive integration method. In the second stage, some ideas of Schläfli and Abrahamson are extended to show that any non-centred orthant probability can be expressed as differences between at most (m−1)! non-centred orthoscheme probabilities. This approach allows an accurate evaluation of many multivariate normal probabilities which have important applications in statistical practice.
Comparing Two Measures of Creatinine Clearance: An Application of Errors-in-Variables and Bootstrap Techniques
Authors: Oman Samuel D. , Meir Natalia , Halm Nissim
Published: March 2003

Two indices of creatinine clearance (an index of kidney function) are compared on a group of cancer patients who underwent chemotherapy with a potentially nephrotoxic drug. The standard index, measured creatinine clearance MCC, is cumbersome to use, whereas the more convenient alternative, estimated creatinine clearance ECC, has not yet been conclusively evaluated on cancer patients. We conclude that under certain clinical conditions ECC and MCC are identically calibrated for males, but not for females, and we obtain estimated true and false positive rates for assessing the use of ECC instead of MCC as a diagnostic tool. We use a model that is formally equivalent to an errors-in-variables model with (unbalanced) repeated observations and correlated measurement errors. The bootstrap is used to obtain standard errors and confidence limits.
Estimating the Propagation Rate of a Viral Infection of Potato Plants via Mixtures of Regressions
Authors: Turner T. Rolf
Published: March 2003

A problem arising from the study of the spread of a viral infection among potato plants by aphids appears to involve a mixture of two linear regressions on a single predictor variable. The plant scientists studying the problem were particularly interested in obtaining a 95% confidence upper bound for the infection rate. We discuss briefly the procedure for fitting mixtures of regression models by means of maximum likelihood, effected via the EM algorithm. We give general expressions for the implementation of the M-step and then address the issue of conducting statistical inference in this context. A technique due to T. A. Louis may be used to estimate the covariance matrix of the parameter estimates by calculating the observed Fisher information matrix. We develop general expressions for the entries of this information matrix. Having the complete covariance matrix permits the calculation of confidence and prediction bands for the fitted model. We also investigate the testing of hypotheses concerning the number of components in the mixture via parametric and ‘semiparametric’ bootstrapping. Finally, we develop a method of producing diagnostic plots of the residuals from a mixture of linear regressions.
Optimal Sampling Times in Population Pharmacokinetic Studies
Authors: Stroud Jonathan R. , Müller Peter , Rosner Gary L.
Published: March 2003

We propose a simulation-based approach to decision theoretic Bayesian optimal design. The underlying probability model is a population pharmacokinetic model which allows for correlated responses (drug concentrations) and patient-to-patient heterogeneity. We consider the problem of choosing sampling times for the anticancer agent paclitaxel, using criteria related to the total area under the curve, the time above a critical threshold and the sampling cost.
Validation of Surrogate end Points in Multiple Randomized Clinical Trials with Failure Time end Points
Authors: Burzykowski Tomasz , Molenberghs Geert , Buyse Marc , Geys Helena , Renard Didier
Published: March 2003

Before a surrogate end point can replace a final (true) end point in the evaluation of an experimental treatment, it must be formally ‘validated’. The validation will typically require large numbers of observations. It is therefore useful to consider situations in which data are available from several randomized experiments. For two normally distributed end points Buyse and co-workers suggested a new definition of validity in terms of the quality of both trial level and individual level associations between the surrogate and true end points. This paper extends this approach to the important case of two failure time end points, using bivariate survival modelling. The method is illustrated by using two actual sets of data from cancer clinical trials.
Modelling Change in Cognitive Understanding with Finite Mixtures
Authors: Thomas Hoben , Hettmansperger Thomas P.
Published: March 2003

Psychological theories often posit the existence of several different states. Individuals are viewed as belonging to one of the states at a given age, but with development pass to another state. A main problem in evaluating such theories is representing the transition from one state to another over age. A stochastic transition framework is proposed which should be useful in many different settings. The model is illustrated with data from a cognitive development task.
Bayesian Modelling of Catch in a North-West Atlantic Fishery
Authors: Fernández Carmen , Ley Eduardo , Steel Mark F. J.
Published: March 2003

We model daily catches of fishing boats in the Grand Bank fishing grounds. We use data on catches per species for a number of vessels collected by the European Union in the context of the Northwest Atlantic Fisheries Organization. Many variables can be thought to influence the amount caught: a number of ship characteristics (such as the size of the ship, the fishing technique used and the mesh size of the nets) are obvious candidates, but one can also consider the season or the actual location of the catch. Our database leads to 28 possible regressors (arising from six continuous variables and four categorical variables, whose 22 levels are treated separately), resulting in a set of 177 million possible linear regression models for the log-catch. Zero observations are modelled separately through a probit model. Inference is based on Bayesian model averaging, using a Markov chain Monte Carlo approach. Particular attention is paid to the prediction of catches for single and aggregated ships.
Correlation-Adjusted Estimation of Sensitivity and Specificity of Two Diagnostic Tests
Authors: Georgiadis Marios P. , Johnson Wesley O. , Gardner Ian A. , Singh Ramanpreet
Published: March 2003

Models for multiple-test screening data generally require the assumption that the tests are independent conditional on disease state. This assumption may be unreasonable, especially when the biological basis of the tests is the same. We propose a model that allows for correlation between two diagnostic test results. Since models that incorporate test correlation involve more parameters than can be estimated with the available data, posterior inferences will depend more heavily on prior distributions, even with large sample sizes. If we have reasonably accurate information about one of the two screening tests (perhaps the standard currently used test) or the prevalences of the populations tested, accurate inferences about all the parameters, including the test correlation, are possible. We present a model for evaluating dependent diagnostic tests and analyse real and simulated data sets. Our analysis shows that, when the tests are correlated, a model that assumes conditional independence can perform very poorly. We recommend that, if the tests are only moderately accurate and measure the same biological responses, researchers use the dependence model for their analyses.
RATE OPTIMAL SEMIPARAMETRIC ESTIMATION OF THE MEMORY PARAMETER OF THE GAUSSIAN TIME SERIES WITH LONG‐RANGE DEPENDENCE
Authors: Giraitis Liudas , Robinson Peter M. , Samarov Alexander
Published: March 2003

There exist several estimators of the memory parameter in long‐ memory time series models with the spectrum specified only locally near zero frequency. In this paper we give an asymptotic lower bound for the minimax risk of any estimator of the memory parameter as a function of the degree of local smoothness of the spectral density at zero. The lower bound allows one to evaluate and compare different estimators by their asymptotic behaviour, and to claim the rate optimality for any estimator attaining the bound. A log‐periodogram regression estimator, analysed by Robinson (Log‐periodogram regression of time series with long range dependence. Ann. Stat. 23 (1995), 1048‐‐72), is then shown to attain the lower bound, and is thus rate optimal.
On threshold moving‐average models
Authors: Gooijer Jan De
Published: March 2003

In this paper the class of discrete self‐exciting threshold moving‐average (SETMA) models is studied in some detail. In particular, we consider various problems associated with the identification, estimation and testing of these models. A simple method for distinguishing between low order moving average (MA) and low order SETMA models is presented. Some simulation results illustrate the performance of the proposed method. We also derive a Lagrange multiplier (LM) test statistic for testing a linear MA model against a SETMA model. The small sample performance of the LM test is evaluated in a Monte Carlo study. A real example is used to illustrate the results.
On the Optimal Segment Length for Parameter Estimates for Locally Stationary Time Series
Authors: Dahlhaus Rainer , Giraitis Liudas
Published: March 2003

We discuss the behaviour of parameter estimates when stationary time series models are fitted locally to non‐stationary processes which have an evolutionary spectral representation. A particular example is the estimation for an autoregressive process with time‐varying coefficients by local Yule–Walker estimates. The bias and the mean squared error for the parameter estimates are calculated and the optimal length of the data segment is determined.
The Beveridge–Nelson Decomposition: A Different Perspective with New Results
Authors: Gomez Victor , Breitung Jorg
Published: March 2003

We show that the decomposition proposed by Beveridge and Nelson (J. Monet. Econ. 7 (1981), 151–74) for models that are integrated of order 1 can be generalized to seasonal autoregressive integrated moving‐average models by means of a partial fraction decomposition. An algorithm which is very fast and easy to implement is proposed to optimally (in the mean squared sense) compute the estimates of the components in the generalized decomposition.
A State‐Space EM Algorithm for Longitudinal Data
Authors: Icaza Gloria , Jones Richard
Published: March 2003

An exact EM algorithm is developed for Gaussian longitudinal mixed models in state‐space form. These models include between‐subject random effects as well as within‐subject serial correlation and possibly observational error. Data for each subject may be equally spaced with missing observations, or unequally spaced with different observation times for different subjects. The method uses the Kalman filter and smoothing algorithm to obtain the conditional expectations of the unobserved data given the observations used in the E step of the EM algorithm. Maximum likelihood estimates of the parameters are obtained wtihout the need to use nonlinear optimization routines. Using simulations, the method is shown to give identical results to maximum likelihood methods that use nonlinear optimization.
Nonparametric Lag Selection for Time Series
Authors: Tschernig Rolf , Yang Lijian
Published: March 2003

A nonparametric version of the Final Prediction Error (FPE) is analysed for lag selection in nonlinear autoregressive time series under very general conditions including heteroskedasticity. We prove consistency and derive probabilities of incorrect selections that have been previously unavailable. Since it is more likely to overfit (have too many lags) than to underfit (miss some lags), a correction factor is proposed to reduce overfitting and hence increase correct fitting. For the FPE calculation, the local linear estimator is introduced in addition to the Nadaraya‐Watson estimator in order to cover a very broad class of processes. To achieve faster computation, a plug‐in band‐width is suggested for the local linear estimator. Our Monte‐Carlo study corroborates that the correction factor generally improves the probability of correct lag selection for both linear and nonlinear processes and that the plug‐in bandwidth works at least as well as its commonly used competitor. The proposed methods are applied to the Canadian lynx data and daily returns of DM/US‐Dollar exchange rates.
Broadband Semiparametric Estimation of the Memory Parameter of a Long‐Memory Time Series Using Fractional Exponential Models
Authors: Hurvich Clifford M. , Brodsky Julia
Published: March 2003

We consider a fractional exponential, or FEXP estimator of the memory parameter of a stationary Gaussian long‐memory time series. The estimator is constructed by fitting a FEXP model of slowly increasing dimension to the log periodogram at all Fourier frequencies by ordinary least squares, and retaining the corresponding estimated memory parameter. We do not assume that the data were necessarily generated by a FEXP model, or by any other finite‐parameter model. We do, however, impose a global differentiability assumption on the spectral density except at the origin. Because of this, and its use of all Fourier frequencies, we refer to the FEXP estimator as a broadband semiparametric estimator. We demonstrate the consistency of the FEXP estimator, and obtain expressions for its asymptotic bias and variance. If the true spectral density is sufficiently smooth, the FEXP estimator can strongly outperform existing semiparametric estimators, such as the Geweke–Porter‐Hudak (GPH) and Gaussian semiparametric estimators (GSE), attaining an asymptotic mean squared error proportional to (log n)/n, where n is the sample size. In a simulation study, we demonstrate the merits of using a finite‐sample correction to the asymptotic variance, and we also explore the possibility of automatically selecting the dimension of the exponential model using Mallows’CL criterion.
Asymptotic laws of successive least squares estimates for seasonal arima models and application
Authors: Truong‐van B. , Varachaud P.
Published: March 2003

Abstract. In view of detecting the stochastic non‐stationarity in time series, successive Yule–Walker estimates are considered for general seasonal ARIMA models and their asymptotic laws are obtained. This extends results known on least squares estimates for stable–unstable ARMA. Furthermore, these asymptotic laws are then compared with analogous results obtained under some additive seasonal model that corresponds to the case of deterministic seasonal behaviour. These results, combined with a simulation study, reveal that successive autoregressions provide a very useful tool both for identifying seasonal ARIMA processes and for distinguishing between stochastic and deterministic seasonal behaviours.
Women's Labour Force Participation and Part Time Work in Spain
Authors: Lázaro Nieves , Moltó Maria‐Luisa , Sánchez Rosario
Published: March 2003

Spain is one of the southern countries where the percentage of women working part‐time is relatively low in comparison to other European countries, together with a low female activity rate. Some important obstacles to increasing female activity rates have already been removed, as younger cohorts of women show a more permanent attachment to the labour force than older women, meeting even high unemployment, which is especially acute for women and young people. Under the recent labour market reform, it is hoped that part‐time contracts, which were first regulated in 1984, would be a way of facilitating flexibility and an incentive for employers to create jobs, as the experience of other countries has shown. The relative novelty of part‐time work in Spain is the reason why this typically female employment regime has not been much explored in Spain yet, in spite of its important role in the reorganisation of the employment system.
Interpreting Gaps in Manpower Forecasting Models
Authors: Borghans Lex , Willems Ed
Published: March 2003

In manpower forecasting labour market developments are analysed in terms of shortages and surpluses. Such an approach seems to neglect the flexibility of the labour market, present in most economic labour market models. It is shown that an appropriate interpretation of gaps in manpower forecasting does not exclude a full functioning of the market clearing mechanism.