bluuebunny/crossref_metadata_2025_split huggingface dataset:
Estimating the causal effects of smoking
Authors: Rubin Donald B. 
Published: August 2002

AbstractAn important application of statistics in recent years has been to address the causal effects of smoking. There is little doubt that there are health risks associated with smoking. However, more general issues concern the causal effects due to the alleged misconduct of the tobacco industry or due to programmes designed to curtail tobacco use. To address any such causal question, assumptions must be made. Although some of the issues are well known in the statistical and epidemiological literature, there does not appear to be a unified treatment that provides prescriptive guidance on the estimation of these causal effects with explication of the needed assumptions. A ‘conduct attributable fraction’ is derived, which allows for arbitrary changes in smoking and non‐smoking health care expenditure related factors in a counterfactual world without the alleged misconduct, and therefore generalizes the traditional ‘smoking attributable fraction’. The formulation presented here, although described for the problem of estimating excess health care expenditures due to the alleged misconduct of the tobacco industry, is more general. It can be applied to any outcome, such as mortality, morbidity, or income from excise taxes, as well as to any situation in which consequences due to alleged misconduct (for example, of two entities, such as the tobacco and the asbestos industries) or due to hypothetical programmes (for example, extra smoking reduction initiatives) are to be estimated. Copyright © 2001 John Wiley & Sons, Ltd.
A mixed effects model for the analysis of ordinal longitudinal pain data subject to informative drop‐out
Authors: Pulkstenis Erik , Ten Have Thomas R. , Landis J. Richard 
Published: August 2002

AbstractWe extend the model of Pulkstenis et al. that models binary longitudinal data, subject to informative drop‐out through remedication, to the ordinal response case. We present a selection model shared‐parameter approach that specifies mixed models for both ordinal response and discrete survival time to remedication. In this fashion, the random parameter present in both models completely characterizes the relationship between response and time to remedication inducing their conditional independence. With a log‐log link function for both response and study ‘survival’, as well as specification of a log‐gamma distribution for the random effect, we obtain a closed‐form expression for the marginal log‐likelihood of response and time to remedication that does not require approximation or numerical integration techniques. A data analysis is performed and simulation results presented which support the consistency of parameter and standard error estimates. Copyright © 2001 John Wiley & Sons, Ltd.
A standardization method to adjust for the effect of patient selection in phase II clinical trials
Authors: Mazumdar Madhu , Fazzari Melissa , Panageas Katherine S. 
Published: August 2002

AbstractNew combination regimens evaluated in phase II cancer clinical trials often show promising results compared to the standard therapy for a disease system. Selection of patients with a better prognosis can be a prominent factor for this optimism. For most disease systems, prognostic variables that are related to the outcome are available and are called risk factors. Patients are classified into risk categories depending on the number of risk factors they possess. The patient distribution is defined as the proportion of patients falling into each of these risk categories. Typically, the patient distribution observed for a phase II study differs from the standard therapy reports so that the outcomes are not comparable. A randomized trial is the ultimate step for establishing the efficacy of a new treatment. In order to determine whether a regimen should progress to a phase III trial, we suggest adjusting the standard therapy outcome for the effect of the observed phase II patient distribution. If the endpoint of interest is tumour response proportion, a weighted average utilizing the standard therapy response proportions and the phase II patient distribution would provide an estimate of the adjusted standard therapy response proportion. Confirmatory phase II trials often attempt to estimate median survival in addition to response proportion, since this is the primary endpoint for most phase III cancer studies. Because data are censored, we propose an adjustment method based on the bootstrap resampling technique. We illustrate the problem of disparate patient selection with data from melanoma studies and demonstrate the usefulness of the proposed adjustment method with data from bladder cancer studies. A simulation study indicates that the magnitude of the adjustment is heavily dependent on the degree of separation of the risk categories. SAS code is available on a website (http://lib.stat.cmu.edu) for easy implementation. Copyright © 2001 John Wiley & Sons, Ltd.
Worm plot: a simple diagnostic device for modelling growth reference curves
Authors: Buuren Stef van , Fredriks Miranda 
Published: August 2002

AbstractThe worm plot visualizes differences between two distributions, conditional on the values of a covariate. Though the worm plot is a general diagnostic tool for the analysis of residuals, this paper focuses on an application in constructing growth reference curves, where the covariate of interest is age. The LMS model of Cole and Green is used to construct reference curves in the Fourth Dutch Growth Study 1997. If the model fits, the measurements in the reference sample follow a standard normal distribution on all ages after a suitably chosen Box–Cox transformation. The coefficients of this transformation are modelled as smooth age‐dependent parameter curves for the median, variation and skewness, respectively. The major modelling task is to choose the appropriate amount of smoothness of each parameter curve. The worm plot assesses the age‐conditional normality of the transformed data under a variety of LMS models. The fit of each parameter curve is closely related to particular features in the worm plot, namely its offset, slope and curvature. Application of the worm plot to the Dutch growth data resulted in satisfactory reference curves for a variety of anthropometric measures. It was found that the LMS method generally models the age‐conditional mean and skewness better than the age‐related deviation and kurtosis. Copyright © 2001 John Wiley & Sons, Ltd.
A methodology for analysing a repeated measures and survival outcome simultaneously
Authors: Rochon James , Gillespie Brenda W. 
Published: August 2002

AbstractA considerable body of literature has arisen over the past 15 years for analysing univariate repeated measures data. It is rare in applied biomedical research, however, for interest to be restricted to a single outcome measure. In previous work, Rochon considered the case of bivariate repeated measures data in which each outcome is a discrete or continuous random variable. A GEE model was prescribed to relate each set of repeated measures to important explanatory variables. The ‘seemingly unrelated regression’ model was then applied to combine the pair of GEE models into an overall analysis framework. In this paper, we extend this approach to the case in which one endpoint is a repeated measures outcome but the second is a survival endpoint. Estimation and hypothesis testing issues are addressed and the methodology is illustrated with an example. Copyright © 2001 John Wiley & Sons, Ltd.
Comparisons of two‐part models with competitors
Authors: Lachenbruch Peter A. 
Published: August 2002

AbstractTwo‐part models arise when there is a clump of 0 observations in a distribution of continuous non‐negative responses. Several methods for comparing two such distributions are available. These include the straightforward application of the z‐test (or t‐test), the Wilcoxon–Mann–Whitney rank sum test, the Kolmogorov–Smirnov test, and three tests that use a 2 degree of freedom χ2 test based on the sum of the test for equality of proportions and a conditional χ2 test for the continuous responses. This conditional test may be the z‐test, the rank sum test, or the χ2 corresponding to the Kolmogorov–Smirnov test. This study compares the size and power of several of these methods. All tests have the appropriate distribution under the null hypothesis if the distribution of the continuous part has finite moments. If it does not, the z‐test has no power to detect any alternatives. It is found that the 2 d.f. tests are superior to the others when the larger proportion of 0 values corresponds to the population with the larger mean. If the reverse holds, the difference in the proportion of zeros reinforces the difference in means and some single‐part models (the rank sum or Kolmogorov–Smirnov) do best. In those cases, the two‐part models are not far behind, although statistically significantly poorer with respect to power. Published in 2001 by John Wiley & Sons, Ltd.
Nagelkerke N, Fidler V, Bernsen R, Borgdorff M, ‘Estimating treatment effects in randomized clinical trials in the presence of non‐compliance’, Statistics in Medicine 2000;19:1849–1864.
Authors: Nagelkerke Nico 
Published: August 2002

AbstractThe original article to which this Correction refers was published in Statistics in Medicine 2000; 19(14):1849–1864.
Estimating prevalence when the true disease status is incompletely ascertained
Authors: Sasieni Peter 
Published: August 2002

AbstractWe discuss the problem of estimating the number of cases not identified in studies of two or more screening tests in which not all individuals are fully evaluated. In particular we consider studies in which only those individuals who are positive on a screening test have a complete diagnosis. We show how to adjust for individuals who are not fully evaluated despite recommendation for referral and for cases not identified among those negative on all screening tests. The assumptions under which these adjustments are valid are discussed. A proposal is made for analysis of studies using three screening tests. Estimation of and inference about the disease prevalence and the test sensitivity when disease status is ascertained on a random sample of those negative on both screening tests is discussed. Copyright © 2001 John Wiley & Sons, Ltd.
A weighted average likelihood ratio test for spatial clustering of disease
Authors: Gangnon Ronald E. , Clayton Murray K. 
Published: August 2002

AbstractWe consider methods proposed for detecting localized spatial clustering. We propose a new test statistic, the weighted average likelihood ratio test, as an alternative to the spatial scan (maximum likelihood ratio) test statistic. Two different types of weights are considered. We propose an unbiased cluster selection criterion and evaluate the bias of the tests through simulation. We also examine the power of the tests through simulations and apply the methods to the well‐known New York leukaemia data. Copyright © 2001 John Wiley & Sons, Ltd.
Meta‐analysis of ordinal outcomes using individual patient data
Authors: Whitehead Anne , Omar Rumana Z. , Higgins Julian P. T. , Savaluny Elly , Turner Rebecca M. , Thompson Simon G. 
Published: August 2002

AbstractMeta‐analyses are being undertaken in an increasing diversity of diseases and conditions, some of which involve outcomes measured on an ordered categorical scale. We consider methodology for undertaking a meta‐analysis on individual patient data for an ordinal response. The approach is based on the proportional odds model, in which the treatment effect is represented by the log‐odds ratio. A general framework is proposed for fixed and random effect models. Tests of the validity of the various assumptions made in the meta‐analysis models, such as a global test of the assumption of proportional odds between treatments, are presented. The combination of studies with different definitions or numbers of response categories is discussed. The methods are illustrated on two data sets, in a classical framework using SAS and MLn and in a Bayesian framework using BUGS. The relative merits of the three software packages for such meta‐analyses are discussed. Copyright © 2001 John Wiley & Sons, Ltd.
Long‐term survivor mixture model with random effects: application to a multi‐centre clinical trial of carcinoma
Authors: Yau Kelvin K. W. , Ng Angus S. K. 
Published: August 2002

AbstractA mixture model incorporating long‐term survivors has been adopted in the field of biostatistics where some individuals may never experience the failure event under study. The surviving fractions may be considered as cured. In most applications, the survival times are assumed to be independent. However, when the survival data are obtained from a multi‐centre clinical trial, it is conceived that the environmental conditions and facilities shared within clinic affects the proportion cured as well as the failure risk for the uncured individuals. It necessitates a long‐term survivor mixture model with random effects. In this paper, the long‐term survivor mixture model is extended for the analysis of multivariate failure time data using the generalized linear mixed model (GLMM) approach. The proposed model is applied to analyse a numerical data set from a multi‐centre clinical trial of carcinoma as an illustration. Some simulation experiments are performed to assess the applicability of the model based on the average biases of the estimates formed. Copyright © 2001 John Wiley & Sons, Ltd.
Sample size requirements for matched case‐control studies of gene–environment interaction
Authors: Gauderman W. James 
Published: August 2002

AbstractConsideration of gene–environment (G×E) interaction is becoming increasingly important in the design of new epidemiologic studies. We present a method for computing required sample size or power to detect G×E interaction in the context of three specific designs: the standard matched case‐control; the case‐sibling, and the case‐parent designs. The method is based on computation of the expected value of the likelihood ratio test statistic, assuming that the data will be analysed using conditional logistic regression. Comparisons of required sample sizes indicate that the family‐based designs (case‐sibling and case‐parent) generally require fewer matched sets than the case‐control design to achieve the same power for detecting a G×E interaction. The case‐sibling design is most efficient when studying a dominant gene, while the case‐parent design is preferred for a recessive gene. Methods are also presented for computing sample size when matched sets are obtained from a stratified population, for example, when the population consists of multiple ethnic groups. A software program that implements the method is freely available, and may be downloaded from the website http://hydra.usc.edu/gxe. Copyright © 2002 John Wiley & Sons, Ltd.
A testing procedure for survival data with few responders
Authors: Freidlin Boris , Korn Edward L. 
Published: August 2002

AbstractIn the course of designing a clinical trial, investigators are often faced with the possibility that only a fraction of the patients will benefit from the experimental treatment. A proper clinical trial design requires prospective specification of the testing procedures to be used in the analysis. In the absence of reliable prognostic factors capable of identifying the appropriate subset of patients, there is a need for a test procedure that will be sensitive to a range of possible fractions of responders. Focusing on survival data, we propose guidelines for selecting a proper test procedure based on the anticipated proportion of responding patients. These guidelines suggest that the logrank test should be used when the fraction of responders is expected to be greater than 0.5, otherwise procedures based on weighted linear rank tests are preferable. Overall this approach provides good power properties when the treatment affects only a small proportion of patients while protecting against substantial loss of power when all patients are affected. Use of the procedure is illustrated with data from two published randomized studies. Published in 2002 by John Wiley & Sons, Ltd.
Repeated measures models for prescribing change
Authors: Sithole Jabulani S. , Jones Peter W. 
Published: August 2002

AbstractLinear mixed models are used to detect a change, if any, in prescribing habits at the primary care practice level due to an educational intervention given repeated measures data before and after intervention and a control group.Inferences are corrected for general practice size, fundholding status and baseline prescribing. The correlation structure is discussed and the results for multilevel modelling using MLwiN and NLME version 3.0 are compared. Copyright © 2002 John Wiley & Sons, Ltd.
Stress prevention training: sex differences in types of stressors, coping, and training effects
Authors: Bekker Marrie H. J. , Nijssen Angelique , Hens Gonnie 
Published: August 2002

AbstractThe present study was aimed at examining the effectiveness of preventive group training and sex differences in types of work stressors, coping strategies, and training effects. Sixty‐eight trainees of stress prevention courses of Regional Institutions for Ambulatory Mental Health Care (RIAGGs) in the Netherlands took part in the study before training (T1), 36 of them after the training (T2), and 3 months later 24 of them (T3). For controlling time effects, a non‐training group was used as the control which had not sought help at a RIAGG nor suffered from stress complaints. Questionnaires were administered at all three time intervals, reflecting health, stress, coping, personality, and perceived job (context) characteristics. After training (T2), the trainees reported significantly less psychological and somatic complaints, less stress, a lower need for recovery after work, the use of more active coping and social support seeking, and a higher capability for managing new situations. The positive effects were maintained at T3. The control group showed no differences between T1 and T2. Women compared with men reported to have less executive tasks and possibilities in their jobs, and less participation and autonomy. Training effects were not affected by being male or female. However, before, as well as after training, women suffered from more health and stress complaints. Future training programmes might be improved by paying attention to sex differences in antecedents as well as consequences of work‐related stress. Copyright © 2001 John Wiley & Sons, Ltd.
Market microstructure in a global B2B network
Authors: Zaheer Srilata , Zaheer Akbar 
Published: August 2002

AbstractOn‐line marketplaces raise several interesting issues, among them the relevance of location when content is digitized, and the assessment of a supplier's capabilities when buyers worldwide only have electronic contact with sellers. In global B2B on‐line marketplaces, market microstructures, i.e. which firms compete for the same customers, are thus likely to be influenced by how customers value location and firm capabilities in their decisions to do business with different suppliers on‐line. We suggest that both these sets of attributes will continue to matter on‐line—firms possessing similar capabilities, as well as firms that are similar in location by country, time zones or clusters, will compete for business from the same customers. We model the similarity in competitive positions between pairs of firms based on the overlap in their customer networks, using data on actual interactions between supplier and customer banks on an electronic trading system. Using QAP network regression techniques on the 100 largest banks in this industry, we find that similarity in capabilities influences who competes with whom, and that location still matters in a global B2B exchange. Interestingly, location influences who a firm's competitors are, but not where its customers are from. Copyright © 2001 John Wiley & Sons, Ltd.
Organizational ownership, competitive intensity, and firm performance: an empirical study of the Indian manufacturing sector
Authors: Ramaswamy Kannan 
Published: August 2002

AbstractEmerging countries are using privatization as a key strategy in their drive to become free market economies. Although these ownership changes are rapidly gaining prominence, the academic literature has been equivocal about the performance benefits of private vs. state ownership. The lack of clarity in findings can be largely traced to the underspecification of the models that prior studies have examined. Specifically, prior studies have mostly ignored the central role of competitive rivalry. This paper proposes a model that centers around the interactive, inseparable effects of ownership and competitive rivalry on firm performance. Results of the empirical examination set in India show that competitive intensity moderates the relationship between ownership and performance. Copyright © 2001 John Wiley & Sons, Ltd.
Real options in equity partnerships
Authors: Folta Timothy B. , Miller Kent D. 
Published: August 2002

AbstractWe examine factors influencing the decision to acquire additional equity in partner firms in research‐intensive industries. This decision involves choosing between flexibility and commitment. Option theory motivates hypotheses regarding the effects of uncertainty, valuation of developing technologies, and the threat of preemptive rivalry. Our main hypothesis is that the resolution of uncertainty for high‐value technologies motivates commitment decisions. We also argue that when the underlying growth option is at risk of preemption by rivals, greater uncertainty encourages commitment. An event history model tests these hypotheses using data from minority investments in the biotechnology industry. Copyright © 2002 John Wiley & Sons, Ltd.
Pay dispersion and workforce performance: moderating effects of incentives and interdependence
Authors: Shaw Jason D. , Gupta Nina , Delery John E. 
Published: August 2002

AbstractThe compensation literature is replete with arguments, but lacking in empirical tests, regarding the effects of pay dispersion on organizational outcomes. Pay dispersion may increase effort and provide incentives for high workforce performance levels, but may also inhibit cooperation and goal orientation among employees. Drawing on several theoretical perspectives (individual motivation, institutional theory, organizational justice, and neoclassical economics), this study predicts that pay dispersion will be associated with higher levels of workforce performance when accompanied by formal individual incentive systems and independent work, while pay compression is desirable in the absence of individual incentive systems and when work is interdependent. Survey research studies in two industrial sectors (the motor carrier and concrete pipe industries) were conducted to address these issues. Interactive regression results were generally supportive of the predictions across several measures of workforce performance (accident rates, safety violations, and productivity). Implications of these studies for strategy implementation in terms of compensation theory and practice are addressed. Copyright © 2002 John Wiley & Sons, Ltd.
Confined types in Java
Authors: Vitek Jan , Bokowski Boris 
Published: August 2002

AbstractThe sharing and transfer of references in object‐oriented languages is difficult to control. Without any constraint, practical experience has shown that even carefully engineered object‐oriented code can be brittle, and subtle security deficiencies can go unnoticed. In this paper, we present inexpensive syntactic constraints that strengthen encapsulation by imposing static restrictions on the spread of references. In particular, we introduceconfined typesto impose a static scoping discipline on dynamic references andanonymous methodsto loosen confinement somewhat to allow code reuse. We have implemented a verifier which performs a modular analysis of Java programs and provides a static guarantee that confinement is respected. Copyright © 2001 John Wiley & Sons, Ltd.