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 Author:
 Shih, Joanna H.; Fay, Michael P.
 Source:
 Biometrics 1999 v.55 no.4 pp. 11561161
 ISSN:
 0006341X
 Subject:
 biometry; simulation models; statistics
 Abstract:
 ... We propose a class of permutation tests for stratified survival data. The tests are derived using the framework of Fay and Shih (1998, Journal of the American Statistical Association93, 387â396), which creates tests by permuting scores based on a functional of estimated distribution functions. Here the estimated distribution function for each possibly rightâ, leftâ, or intervalâcensored ob ...
 DOI:
 10.1111/j.0006341X.1999.01156.x

http://dx.doi.org/10.1111/j.0006341X.1999.01156.x
 Author:
 Senn, Stephen; Grieve, Andrew P.
 Source:
 Biometrics 1999 v.55 no.4 pp. 13141315
 ISSN:
 0006341X
 Subject:
 biometry; clinical trials; drugs
 Abstract:
 ... A method purporting to provide optimal allocations in bioequivalence studies fails to do so on both statistical and practical grounds. Reasons as to why this is so are given. ...
 DOI:
 10.1111/j.0006341X.1999.01314.x

http://dx.doi.org/10.1111/j.0006341X.1999.01314.x
 Author:
 Lehmacher, Walter; Wassmer, Gernot
 Source:
 Biometrics 1999 v.55 no.4 pp. 12861290
 ISSN:
 0006341X
 Subject:
 biometry; clinical trials; drugs
 Abstract:
 ... A method for group sequential trials that is based on the inverse normal method for combining the results of the separate stages is proposed. Without exaggerating the Type I error rate, this method enables dataâdriven sample size reassessments during the course of the study. It uses the stopping boundaries of the classical group sequential tests. Furthermore, exact test procedures may be derived ...
 DOI:
 10.1111/j.0006341X.1999.01286.x

http://dx.doi.org/10.1111/j.0006341X.1999.01286.x
 Author:
 Auranen, Kari; Eichner, Martin; KÃ¤yhty, Helena; Takala, Aino K.; Arjas , Elja
 Source:
 Biometrics 1999 v.55 no.4 pp. 13061313
 ISSN:
 0006341X
 Subject:
 Haemophilus influenzae; Markov chain; Monte Carlo method; antibodies; bacteria; biometry; blood serum; immunity; models; regression analysis
 Abstract:
 ... A hierarchical Bayesian regression model is fitted to longitudinal data on Haemophilus influenzae type b (Hib) serum antibodies. To estimate the decline rate of the antibody concentration, the model accommodates the possibility of unobserved subclinical infections with Hib bacteria that cause increasing concentrations during the study period. The computations rely on Markov chain Monte Carlo simul ...
 DOI:
 10.1111/j.0006341X.1999.01306.x

http://dx.doi.org/10.1111/j.0006341X.1999.01306.x
 Author:
 Bartoletti, Stefania; Flury, Bernard D.; Nel, Daan G.
 Source:
 Biometrics 1999 v.55 no.4 pp. 12101214
 ISSN:
 0006341X
 Subject:
 allometry; biometry; covariance; models
 Abstract:
 ... Constants of allometric growth are commonly estimated by the first eigenvector of the covariance matrix of log measurements. Hills (1982, in Encyclopedia of Statistical Sciences, 48â54) defines a model of allometric extension for two related species by the conditions that (a) the constants of allometric growth are identical for both species and (b) the vector of mean differences is proportional ...
 DOI:
 10.1111/j.0006341X.1999.01210.x

http://dx.doi.org/10.1111/j.0006341X.1999.01210.x
 Author:
 Albert, Paul S.
 Source:
 Biometrics 1999 v.55 no.4 pp. 12521257
 ISSN:
 0006341X
 Subject:
 algorithms; asthma; biological resistance; biometry; blood pressure; chronic diseases; disease incidence; emotions; heart; hypertension; lung function; models; people
 Abstract:
 ... Studies of chronic disease often focus on estimating prevalence and incidence in which the presence of active disease is based on dichotomizing a continuous marker variable measured with error. Examples include hypertension, asthma, and depression, where active disease is defined by setting a threshold on a continuous measure of blood pressure, respiratory function, and mood, respectively. This pa ...
 DOI:
 10.1111/j.0006341X.1999.01252.x

http://dx.doi.org/10.1111/j.0006341X.1999.01252.x
 Author:
 Follmann, Dean A.; Proschan, Michael A.
 Source:
 Biometrics 1999 v.55 no.4 pp. 11511155
 ISSN:
 0006341X
 Subject:
 biometry; clinical trials; disease severity; patients; regression analysis; risk factors
 Abstract:
 ... An important issue in clinical trials is whether the effect of treatment is essentially homogeneous as a function of baseline covariates. Covariates that have the potential for an interaction with treatment may be suspected on the basis of treatment mechanism or may be known risk factors, as it is often thought that the sickest patients may benefit most from treatment. If disease severity is more ...
 DOI:
 10.1111/j.0006341X.1999.01151.x

http://dx.doi.org/10.1111/j.0006341X.1999.01151.x
 Author:
 Grigoletto, Matteo; Akritas, Michael G.
 Source:
 Biometrics 1999 v.55 no.4 pp. 11771187
 ISSN:
 0006341X
 Subject:
 biometry; confidence interval; covariance; data collection; least squares; models; risk
 Abstract:
 ... We propose a method for fitting semiparametric models such as the proportional hazards (PH), additive risks (AR), and proportional odds (PO) models. Each of these semiparametric models implies that some transformation of the conditional cumulative hazard function (at each t) depends linearly on the covariates. The proposed method is based on nonparametric estimation of the conditional cumulative h ...
 DOI:
 10.1111/j.0006341X.1999.01177.x

http://dx.doi.org/10.1111/j.0006341X.1999.01177.x
 Author:
 Reiczigel, JenÃ¶
 Source:
 Biometrics 1999 v.55 no.4 pp. 10591063
 ISSN:
 0006341X
 Subject:
 biometry; data analysis; simulation models
 Abstract:
 ... Experimental data often consist of serial measurements on subjects after a treatment. Typical questions concerning such data are: (A) Do subjects really react to treatment or are the fluctuations just random? (B) What are the numerical characteristics of the response? (C) Is the response identical in all groups? Differences between the individuals in the dynamics of the reaction make it difficult ...
 DOI:
 10.1111/j.0006341X.1999.01059.x

http://dx.doi.org/10.1111/j.0006341X.1999.01059.x
 Author:
 Royston, Patrick; Ferreira, Alberto
 Source:
 Biometrics 1999 v.55 no.4 pp. 10051013
 ISSN:
 0006341X
 Subject:
 algorithms; biometry; conception; data collection; models; probability
 Abstract:
 ... Standard conception probabilities models assume that different acts of intercourse make independent contributions to the probability of conception in viable cycles. We propose an alternative, approximate model based on the assumption that the act of intercourse closest to the time of maximum fertility is the one most likely to have caused conception. We describe an adaptive algorithm [the most fer ...
 DOI:
 10.1111/j.0006341X.1999.01005.x

http://dx.doi.org/10.1111/j.0006341X.1999.01005.x
 Author:
 Regal, Ronald R.; Hook, Ernest B.
 Source:
 Biometrics 1999 v.55 no.4 pp. 12411246
 ISSN:
 0006341X
 Subject:
 biometry; epidemiological studies; population size; spina bifida; New York
 Abstract:
 ... An exact conditional test for an Mâway logâlinear interaction in a fully observed 2M contingency table is formulated. Prom this is derived a procedure for interval estimation of the total count N in a 2 M contingency table, one of whose entries is unobserved. This procedure has an immediate application to interval estimation of the size of a closed population from incomplete, overlapping lists ...
 DOI:
 10.1111/j.0006341X.1999.01241.x

http://dx.doi.org/10.1111/j.0006341X.1999.01241.x
 Author:
 Langholz, Bryan; Ziogas, Argyrios; Thomas, Duncan C.; Faucett, Cheryl; Huberman, Mark; Goldstein, Larry
 Source:
 Biometrics 1999 v.55 no.4 pp. 11291136
 ISSN:
 0006341X
 Subject:
 biometry; casecontrol studies; children; diabetes
 Abstract:
 ... Motivated by a Finnish case‐control study of early onset diabetes in which diabetic children are matched to sibling controls, we investigate ascertainment bias of the usual rate ratio estimator from case‐control data under simplex complete ascertainment of families during a fixed interval of time. Analytic results indicate that the assumptions necessary for valid estimation are that the disease is ...
 DOI:
 10.1111/j.0006341X.1999.01129.x

http://dx.doi.org/10.1111/j.0006341X.1999.01129.x
 Author:
 Erkanli , Alaattin; Soyer, Refik; Costello, Elizabeth J.
 Source:
 Biometrics 1999 v.55 no.4 pp. 11451150
 ISSN:
 0006341X
 Subject:
 Bayesian theory; Markov chain; Monte Carlo method; adolescents; alcohols; biometry; drugs; models; screening; Great Smoky Mountain region
 Abstract:
 ... We consider Bayesian inference and model selection for prevalence estimation using a longitudinal twoâphase design in which subjects initially receive a lowâcost screening test followed by an expensive diagnostic test conducted on several occasions. The change in the subject's diagnostic probability over time is described using four mixedâeffects probit models in which the subjectâspecific ...
 DOI:
 10.1111/j.0006341X.1999.01145.x

http://dx.doi.org/10.1111/j.0006341X.1999.01145.x
 Author:
 Mallick, Bani K.; Denison, David G. T.; Smith, Adrian F. M.
 Source:
 Biometrics 1999 v.55 no.4 pp. 10711077
 ISSN:
 0006341X
 Subject:
 Markov chain; algorithms; biometry; models
 Abstract:
 ... A Bayesian multivariate adaptive regression spline fitting approach is used to model univariate and multivariate survival data with censoring. The possible models contain the proportional hazards model as a subclass and automatically detect departures from this. A reversible jump Markov chain Monte Carlo algorithm is described to obtain the estimate of the hazard function as well as the survival c ...
 DOI:
 10.1111/j.0006341X.1999.01071.x

http://dx.doi.org/10.1111/j.0006341X.1999.01071.x
 Author:
 Zhang, Heping; Zelterman, Daniel
 Source:
 Biometrics 1999 v.55 no.4 pp. 12471251
 ISSN:
 0006341X
 Subject:
 biometry; carcinogens; disease incidence; mice; models; risk; risk factors
 Abstract:
 ... We describe models for binary valued data to be used to explain the incidence of disease given the level of a known risk factor. Every individual has an unobservable tolerance of the risk. Risk levels below the individual tolerance do not increase the disease incidence above the background, unexposed rate. We estimate parameters from both the tolerance distribution and the risk function for a larg ...
 DOI:
 10.1111/j.0006341X.1999.01247.x

http://dx.doi.org/10.1111/j.0006341X.1999.01247.x
 Author:
 Tang, Dei‐In; Geller, Nancy L.
 Source:
 Biometrics 1999 v.55 no.4 pp. 11881192
 ISSN:
 0006341X
 Subject:
 clinical trials; drug therapy; humans; monitoring; new methods; respiratory tract diseases
 Abstract:
 ... A simple approach is given for conducting closed testing in clinical trials with multiple end‐points in which group sequential monitoring is planned. The approach allows a flexible stopping time; the earliest and latest stopping times are described. The paradigm is applicable both to clinical trials with multiple endpoints and to the one‐sided multiple comparison problem of several treatments vers ...
 DOI:
 10.1111/j.0006341X.1999.01188.x

http://dx.doi.org/10.1111/j.0006341X.1999.01188.x
 Author:
 Shen, Yu; Cheng, S. C.
 Source:
 Biometrics 1999 v.55 no.4 pp. 10931100
 ISSN:
 0006341X
 Subject:
 biometry; confidence interval; data collection; melanoma; models; patients; risk; risk factors
 Abstract:
 ... In the context of competing risks, the cumulative incidence function is often used to summarize the causeâspecific failureâtime data. As an alternative to the proportional hazards model, the additive risk model is used to investigate covariate effects by specifying that the subjectâspecific hazard function is the sum of a baseline hazard function and a regression function of covariates. Base ...
 DOI:
 10.1111/j.0006341X.1999.01093.x

http://dx.doi.org/10.1111/j.0006341X.1999.01093.x
 Author:
 Holcroft, Christina A.; Spiegelman, Donna
 Source:
 Biometrics 1999 v.55 no.4 pp. 11931201
 ISSN:
 0006341X
 Subject:
 biometry; odds ratio; variance
 Abstract:
 ... We compared several validation study designs for estimating the odds ratio of disease with misclassified exposure. We assumed that the outcome and misclassified binary covariate are available and that the errorâfree binary covariate is measured in a subsample, the validation sample. We considered designs in which the total size of the validation sample is fixed and the probability of selection i ...
 DOI:
 10.1111/j.0006341X.1999.01193.x

http://dx.doi.org/10.1111/j.0006341X.1999.01193.x
 Author:
 Zhao, Hongwei; Tsiatis, Anastasios A.
 Source:
 Biometrics 1999 v.55 no.4 pp. 11011107
 ISSN:
 0006341X
 Subject:
 biometry; breast neoplasms; chronic diseases; clinical trials; data collection; patients; quality of life
 Abstract:
 ... Quality of life is an important aspect in evaluation of clinical trials of chronic diseases, such as cancer and AIDS. Qualityâadjusted survival analysis is a method that combines both the quantity and quality of a patient's life into one single measure. In this paper, we discuss the efficiency of weighted estimators for the distribution of qualityâadjusted survival time. Using the general repr ...
 DOI:
 10.1111/j.0006341X.1999.01101.x

http://dx.doi.org/10.1111/j.0006341X.1999.01101.x
 Author:
 Chen, D. G.; Carter, E. M.; Hubert, J. J.; Kim, P. T.
 Source:
 Biometrics 1999 v.55 no.4 pp. 10381043
 ISSN:
 0006341X
 Subject:
 bioassays; biometry; shrinkage; variance
 Abstract:
 ... This article presents a new empirical Bayes estimator (EBE) and a shrinkage estimator for determining the relative potency from several multivariate bioassays by incorporating prior information on the model parameters based on Jeffreys' rules. The EBE can account for any extra variability among the bioassays, and if this extra variability is 0, then the EBE reduces to the maximum likelihood estima ...
 DOI:
 10.1111/j.0006341X.1999.01038.x

http://dx.doi.org/10.1111/j.0006341X.1999.01038.x