bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Comparison of Suicide Patterns in Australia and Hong Kong
Authors: Lloyd Chris J. , Yip Paul S. F. 
Published: March 2003

Summary
We analyse the patterns of 6564 suicides in Hong Kong and 23671 suicides in Australia for the period 1981–1993. Within the unifying framework of logistic regression we investigate how suicide rates vary with marital status and age and how these patterns vary over time and between the two cultures. The main significant differences between the two cultures are that rates are higher in Australia, rates for males are much higher than for females in Australia but only slightly higher in Hong Kong, in Hong Kong the oldest age group has the highest suicide rate unlike in Australia and the protective effects of marriage are larger in Australia.
Screening for Prostate Cancer by Using Random-Effects Models
Authors: Brant Larry J. , Sheng Shan L. , Morrell Christopher H. , Verbeke Geert N. , Lesaffre Emmanuel , Carter H. Ballentine 
Published: March 2003

SummaryRandom-effects models are used to screen male participants in a long-term longitudinal study for prostate cancer. By using posterior probabilities, each male can be classified into one of four diagnostic states for prostate disease: normal, benign prostatic hyperplasia, local cancer and metastatic cancer. Repeated measurements of prostate-specific antigen, collected when there was no clinical evidence of prostate disease, are used in the classification process. An individual's screening data are considered one repeated measurement at a time as his data are collected longitudinally over time. Posterior probabilities are calculated on the basis of data from other individuals with confirmed diagnoses of each of the four diagnostic states.
Random-Digit Dialling in the UK: Viability Revisited
Authors: Nicolaas Gerry , Lynn Peter 
Published: March 2003

SummaryA main obstacle to using telephone methods for social surveys in the UK has been the inability to select a representative and unbiased probability sample of the general population. However, recent changes in the UK telephone numbering system and advances in telephony software appear to provide the means for using random-digit dialling (RDD). This paper presents the results of a study designed to test the feasibility of RDD. The focus is on the sampling method, but we also assess other aspects of the RDD survey method, in the context of a total survey error framework. Although we conclude that RDD is now a viable survey method in the UK, further research and development is advocated to improve the efficiency of fieldwork and response rates.
Generalized Score Test of Homogeneity Based on Correlated Random Effects Models
Authors: Commenges D. , Jacqmin-Gadda H. 
Published: March 2003

Summary
We present a family of tests based on correlated random effects models which provides a synthesis and a generalization of recent work on homogeneity testing. In these models each subject has a particular random effect, but the random effects between subjects are correlated. We derive the general form of the score statistic for testing that the random effects have a variance equal to 0. We apply this result to both parametric and semi-parametric models. In both cases we show that under certain conditions the score statistic has an asymptotic normal distribution. We consider several applications of this theory, including overdispersion, heterogeneity between groups, spatial correlations and genetic linkage.
Multistage Sampling Designs and Estimating Equations
Authors: Whittemore Alice S. 
Published: March 2003

Summary
In some applications it is cost efficient to sample data in two or more stages. In the first stage a simple random sample is drawn and then stratified according to some easily measured attribute. In each subsequent stage a random subset of previously selected units is sampled for more detailed and costly observation, with a unit’s sampling probability determined by its attributes as observed in the previous stages. This paper describes multistage sampling designs and estimating equations based on the resulting data. Maximum likelihood estimates (MLEs) and their asymptotic variances are given for designs using parametric models. Horvitz–Thompson estimates are introduced as alternatives to MLEs, their asymptotic distributions are derived and their strengths and weaknesses are evaluated. The designs and the estimates are illustrated with data on corn production.
Perfect Simulation of Conditionally Specified Models
Authors: Møller Jesper 
Published: March 2003

Summary
We discuss how the ideas of producing perfect simulations based on coupling from the past for finite state space models naturally extend to multivariate distributions with infinite or uncountable state spaces such as auto-gamma, auto-Poisson and autonegative binomial models, using Gibbs sampling in combination with sandwiching methods originally introduced for perfect simulation of point processes.
Multivariate Bandwidth Selection for Local Linear Regression
Authors: Yang Lijian , Tschernig Rolf 
Published: March 2003

Summary
The existence and properties of optimal bandwidths for multivariate local linear regression are established, using either a scalar bandwidth for all regressors or a diagonal bandwidth vector that has a different bandwidth for each regressor. Both involve functionals of the derivatives of the unknown multivariate regression function. Estimating these functionals is difficult primarily because they contain multivariate derivatives. In this paper, an estimator of the multivariate second derivative is obtained via local cubic regression with most cross-terms left out. This estimator has the optimal rate of convergence but is simpler and uses much less computing time than the full local estimator. Using this as a pilot estimator, we obtain plug-in formulae for the optimal bandwidth, both scalar and diagonal, for multivariate local linear regression. As a simpler alternative, we also provide rule-of-thumb bandwidth selectors. All these bandwidths have satisfactory performance in our simulation study.
A Class of Weighted Dependence Measures for Bivariate Failure Time Data
Authors: Fan Juanjuan , Prentice Ross L. , Hsu Li 
Published: March 2003

Summary
This paper considers a class of summary measures of the dependence between a pair of failure time variables over a finite follow-up region. The class consists of measures that are weighted averages of local dependence measures, and includes the cross-ratio-measure and finite region version of Kendall's τ; recently proposed by the authors. Two new special cases are identified that can avoid the need to estimate the bivariate survivor function and that admit explicit variance estimators. Nonparametric estimators of such dependence measures are proposed and are shown to be consistent and asymptotically normal with variances that can be consistently estimated. Properties of selected estimators are evaluated in a simulation study, and the method is illustrated through an analysis of Australian Twin Study data.
Standard Errors for EM Estimation
Authors: Jamshidian Mortaza , Jennrich R. I. 
Published: March 2003

Summary
The EM algorithm is a popular method for computing maximum likelihood estimates. One of its drawbacks is that it does not produce standard errors as a by-product. We consider obtaining standard errors by numerical differentiation. Two approaches are considered. The first differentiates the Fisher score vector to yield the Hessian of the log-likelihood. The second differentiates the EM operator and uses an identity that relates its derivative to the Hessian of the log-likelihood. The well-known SEM algorithm uses the second approach. We consider three additional algorithms: one that uses the first approach and two that use the second. We evaluate the complexity and precision of these three and the SEM in algorithm seven examples. The first is a single-parameter example used to give insight. The others are three examples in each of two areas of EM application: Poisson mixture models and the estimation of covariance from incomplete data. The examples show that there are algorithms that are much simpler and more accurate than the SEM algorithm. Hopefully their simplicity will increase the availability of standard error estimates in EM applications. It is shown that, as previously conjectured, a symmetry diagnostic can accurately estimate errors arising from numerical differentiation. Some issues related to the speed of the EM algorithm and algorithms that differentiate the EM operator are identified.
A Unified Approach to Regression Analysis Under Double-Sampling Designs
Authors: Chen Yi-Hau , Chen Hung 
Published: March 2003

Summary
We propose a unified approach to the estimation of regression parameters under double-sampling designs, in which a primary sample consisting of data on the rough or proxy measures for the response and/or explanatory variables as well as a validation subsample consisting of data on the exact measurements are available. We assume that the validation sample is a simple random subsample from the primary sample. Our proposal utilizes a specific parametric model to extract the partial information contained in the primary sample. The resulting estimator is consistent even if such a model is misspecified, and it achieves higher asymptotic efficiency than the estimator based only on the validation data. Specific cases are discussed to illustrate the application of the estimator proposed.
The Peculiar Shrinkage Properties of Partial Least Squares Regression
Authors: Butler Neil A. , Denham Michael C. 
Published: March 2003

Summary
Partial least squares regression has been widely adopted within some areas as a useful alternative to ordinary least squares regression in the manner of other shrinkage methods such as principal components regression and ridge regression. In this paper we examine the nature of this shrinkage and demonstrate that partial least squares regression exhibits some undesirable properties.
Almost Nonparametric Inference for Repeated Measures in Mixture Models
Authors: Hettmansperger T. P. , Thomas Hoben 
Published: March 2003

Summary
We consider ways to estimate the mixing proportions in a finite mixture distribution or to estimate the number of components of the mixture distribution without making parametric assumptions about the component distributions. We require a vector of observations on each subject. This vector is mapped into a vector of 0s and 1s and summed. The resulting distribution of sums can be modelled as a mixture of binomials. We then work with the binomial mixture. The efficiency and robustness of this method are compared with the strategy of assuming multivariate normal mixtures when, typically, the true underlying mixture distribution is different. It is shown that in many cases the approach based on simple binomial mixtures is superior.
A Diagnostic for Selecting the Threshold in Extreme Value Analysis
Authors: Guillou Armelle , Hall Peter 
Published: March 2003

Summary
A new approach is suggested for choosing the threshold when fitting the Hill estimator of a tail exponent to extreme value data. Our method is based on an easily computed diagnostic, which in turn is founded directly on the Hill estimator itself, ‘symmetrized’ to remove the effect of the tail exponent but designed to emphasize biases in estimates of that exponent. The attractions of the method are its accuracy, its simplicity and the generality with which it applies. This generality implies that the technique has somewhat different goals from more conventional approaches, which are designed to accommodate the minor component of a postulated two-component Pareto mixture. Our approach does not rely on the second component being Pareto distributed. Nevertheless, in the conventional setting it performs competitively with recently proposed methods, and in more general cases it achieves optimal rates of convergence. A by-product of our development is a very simple and practicable exponential approximation to the distribution of the Hill estimator under departures from the Pareto distribution.
Time Series Forecasting with Neural Networks: A Comparative Study Using the Air Line Data
Authors: Faraway Julian , Chatfield Chris 
Published: March 2003

SUMMARY
This case-study fits a variety of neural network (NN) models to the well-known air line data and compares the resulting forecasts with those obtained from the Box–Jenkins and Holt–Winters methods. Many potential problems in fitting NN models were revealed such as the possibility that the fitting routine may not converge or may converge to a local minimum. Moreover it was found that an NN model which fits well may give poor out-of-sample forecasts. Thus we think it is unwise to apply NN models blindly in ‘black box’ mode as has sometimes been suggested. Rather, the wise analyst needs to use traditional modelling skills to select a good NN model, e.g. to select appropriate lagged variables as the ‘inputs’. The Bayesian information criterion is preferred to Akaike’s information criterion for comparing different models. Methods of examining the response surface implied by an NN model are examined and compared with the results of alternative nonparametric procedures using generalized additive models and projection pursuit regression. The latter imposes less structure on the model and is arguably easier to understand.
Information on Sexual Behaviour when some Data are Missing
Authors: Raab G. M. , Donnelly C. A. 
Published: March 2003

SUMMARY
When tables contain missing values, statistical models that allow the non-response probability to be a function of the intended response have been proposed by several researchers. We investigate the properties of these methods in the context of a survey of the sexual behaviour of university students. Profile likelihoods can be computed, even when models are not identified and saturated profile likelihoods (making no assumptions about the non-response mechanism) are derived. Bayesian approaches are investigated and it is shown that their results may be highly sensitive to the prior specification. The proportion of responders answering ‘yes’ to the question ‘have you ever had sexual intercourse?’ was 73%. However, different assumptions about the non-responders gave proportions as low as 46% or as high as 83%. Our preferred estimate, derived from the response-saturated profile likelihood, is 67% with a 95% confidence interval of 58–74%. This is in line with other studies on response bias in the reports of young people’s sexual behaviour that suggest that the respondents overrepresent the sexually active.
Bayesian Sample Size Determination for Estimating Binomial Parameters from Data Subject to Misclassification
Authors: Rahme Elham , Joseph Lawrence , Gyorkos Theresa W. 
Published: March 2003

SUMMARY
We investigate the sample size problem when a binomial parameter is to be estimated, but some degree of misclassification is possible. The problem is especially challenging when the degree to which misclassification occurs is not exactly known. Motivated by a Canadian survey of the prevalence of toxoplasmosis infection in pregnant women, we examine the situation where it is desired that a marginal posterior credible interval for the prevalence of width w has coverage 1−α, using a Bayesian sample size criterion. The degree to which the misclassification probabilities are known a priori can have a very large effect on sample size requirements, and in some cases achieving a coverage of 1−α is impossible, even with an infinite sample size. Therefore, investigators must carefully evaluate the degree to which misclassification can occur when estimating sample size requirements.
Bayesian Analysis of Multivariate Mortality Data with Large Families
Authors: Chen Ming-Hui , Dey Dipak K. , Sinha Debajyoti 
Published: March 2003

SUMMARY
This paper presents a Bayesian method for the analysis of toxicological multivariate mortality data when the discrete mortality rate for each family of subjects at a given time depends on familial random effects and the toxicity level experienced by the family. Our aim is to model and analyse one set of such multivariate mortality data with large family sizes: the potassium thiocyanate (KSCN) tainted fish tank data of O’Hara Hines. The model used is based on a discretized hazard with additional time-varying familial random effects. A similar previous study (using sodium thiocyanate (NaSCN)) is used to construct a prior for the parameters in the current study. A simulation-based approach is used to compute posterior estimates of the model parameters and mortality rates and several other quantities of interest. Recent tools in Bayesian model diagnostics and variable subset selection have been incorporated to verify important modelling assumptions regarding the effects of time and heterogeneity among the families on the mortality rate. Further, Bayesian methods using predictive distributions are used for comparing several plausible models.
Regression Analysis of Health Care Charges with Heteroscedasticity
Authors: Zhou Xiao-Hua , Stroupe Kevin T. , Tierney William M. 
Published: March 2003

SUMMARY
We examine the effects of a prospective drug utilization review and patients’ characteristics on total in-patient and out-patient health care charges. Our analysis of charges is complicated by the fact that the total health care charges are skewed. A log-transformation of these charges can normalize their distribution but may not stabilize their variance. To handle these problems, we propose a linear regression model with a non-constant variance (heteroscedasticity). Using results from a fitted linear regression model for log-transformed charges, we also discuss interpreting the regression coefficients in the original scale and estimating the total health care charges to individual patients. Employing these methods, we analyse total health care charges for drug utilization review patients with hypertension and identify patients’ factors that are related to their total health care charges.
Bayesian Analysis of Competing Risks with Partially Masked Cause of Failure
Authors: Basu Sanjib , Sen Ananda , Banerjee Mousumi 
Published: March 2003

SummaryBayesian analysis of system failure data from engineering applications under a competing risks framework is considered when the cause of failure may not have been exactly identified but has only been narrowed down to a subset of all potential risks. In statistical literature, such data are termed masked failure data. In addition to masking, failure times could be right censored owing to the removal of prototypes at a prespecified time or could be interval censored in the case of periodically acquired readings. In this setting, a general Bayesian formulation is investigated that includes most commonly used parametric lifetime distributions and that is sufficiently flexible to handle complex forms of censoring. The methodology is illustrated in two engineering applications with a special focus on model comparison issues.
Polyvariograms and their Asymptotes
Authors: Chen Z. G. , Anderson O. D. 
Published: March 2003

A definition of a polyvariogram (PV) γb(h)(h = 1, 2, ...) of order b (b≥ max(0, d− 1) is suggested for time series {Z(t})} satisfying {∇d(Z(t) = W(t) (where d is a non‐negative integer and {W(t)} is a second‐order stationary time series and is not over‐differenced). When b = 0, 1 and 2, this definition corresponds to Cressie's (J. Am. Stat. Assoc. 83 (1988), 1108–16; 85 (1990), 272) semivariogram linvariogram and quadvariogram respectively and is simpler. Under very general conditions about {W(t)}, we obtain the relationship between γb(h) and the autocovariance function of {W(t)} and show that the asymptote of γb(h) is a straight line having a positive slope when b = d− 1 and levelling out when b≥d.A definition of a sample polyvariogram (SPV) of order b is given and is shown to be an unbiased and consistent estimate of the PV; and further, some uniformly (in h) almost sure convergence rates are obtained. These properties provide theoretical support for using the SPV to replace the practically unknown PV and generalize the guidelines for identifying d given by Cressie, where {W(t)} was restricted to a white noise and b≤ 2. Some further asymptotic theorems and avenues for using them for statistically testing d and parameters of models for {W(t)} are briefly introduced.
Putnam's Progress: Navigating between Strident Realism and Extreme Skepticism with a Wittgensteinian Chart, an Austinian Spyglass, and a Deweyan Compass
Authors: Munitz Charles 
Published: March 2003

Books reviewed in this article:Hilary Putnam, Pragmatism: An Open QuestionHilary Putnam, The Threefold Cord: Mind, Body, World
Risky Parental Behavior and Adolescent Sexual Activity at First Coitus
Authors: Wilder Esther I. , Watt Toni Terling 
Published: March 2003

In comparison with other industrialized countries, the United States has exceptionally high rates of adolescent pregnancy and abortion. In 1999, nearly half of high‐school students reported having had sexual intercourse, and 6 percent said they had been pregnant or gotten someone pregnant (CDC 2000). American adolescents are especially unlikely to use birth control, and those who do practice contraception tend to rely on inefficient methods (Forrest 1990).Sexual behavior at first intercourse is of particular interest because early entry into sexual activity is associated with contraceptive nonuse and a heightened risk of pregnancy (Abma and Sonenstein 2001; Koenig and Zelnik 1982; Zabin, Kantner, and Zelnik 1979). Moreover, the timing of first intercourse may be a useful marker for risky sexual behavior and a history of sexually transmitted diseases (Greenberg, Magder, and Aral 1992). For example, age at first intercourse is inversely associated with the number of lifetime sexual partners (McGuire et al. 1992).Data from the National Longitudinal Study of Adolescent Health (Add Health) were used to examine the impact of parents' behavior on adolescents' sexual experience and contraceptive use. All else being equal, adolescents whose parents engage in risky behaviors are especially likely to be sexually active and to have had sex before age 15. These findings are only partly attributable to the link between parents' risky behaviors (smoking, drinking, driving without seatbelts) and adolescents' risky behaviors (smoking, drinking, delinquent activity, association with substance‐using peers). Although parental behaviors are effective predictors of adolescents' sexual activity, they are not effective predictors of contraceptive use or of method choice at first coitus. Overall, parents with low levels of self‐efficacy seem to be especially likely to have children at risk of engaging in problem behaviors.