摘要:

Individual bioequivalence has received much attention in the recent literature. One wants to determine whether it is suitable for a given individual to switch formulations from a reference drug to a test drug. Some researchers have argued that the formulation means, subject-by-formulation interaction, and within-subject variances should be included in a single measurement of inequivalence, and due to the complexity of the hypotheses there is a need to use a 2 × 3 or even higher-order crossover design for studies of this type. In this article exact level-αtests are first provided under normality assumptions, and a 2 × 3 crossover design is shown to be sufficient for assessing individual bioequivalence. Some simulations for the proposed test and two examples are presented.

ISSN:0162-1459    

DOI:10.1080/01621459.1999.10474193

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

In comparing the effectiveness of two treatments, suppose that for each patient repeated measurements of an outcome variable are taken at prespecified time points, but some observations may be missing due to the patient's dependent right censoring. In this article, a simple rank estimation procedure, constructed based on an artificial censoring technique, is proposed for the treatment differences over time without imposing a parametric structure on the dependence between the outcome measures and the censoring variable. Our method can be easily implemented and is illustrated by a dataset from an AIDS clinical trial.

ISSN:0162-1459    

DOI:10.1080/01621459.1999.10474194

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

Nonparametric maximum likelihood (NPML) is used to estimate regression parameters in a proportional hazards regression model with missing covariates. The NPML estimator is shown to be consistent and asymptotically normally distributed under some conditions. EM type algorithms are applied to solve the maximization problem. Variance estimates of the regression parameters are obtained by a profile likelihood approach that uses EM-aided numerical differentiation. Simulation results indicate that the NPML estimates of the regression parameters are more efficient than the approximate partial likelihood estimates and estimates from complete-case analysis when missing covariates are missing completely at random, and that the proposed method corrects for bias when the missing covariates are missing at random.

ISSN:0162-1459    

DOI:10.1080/01621459.1999.10474195

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

We consider Bayesian methods for right-censored survival data for populations with a surviving (cure) fraction. We propose a model that is quite different from the standard mixture model for cure rates. We provide a natural motivation and interpretation of the model and derive several novel properties of it. First, we show that the model has a proportional hazards structure, with the covariates depending naturally on the cure rate. Second, we derive several properties of the hazard function for the proposed model and establish mathematical relationships with the mixture model for cure rates. Prior elicitation is discussed in detail, and classes of noninformative and informative prior distributions are proposed. Several theoretical properties of the proposed priors and resulting posteriors are derived, and comparisons are made to the standard mixture model. A real dataset from a melanoma clinical trial is discussed in detail.

ISSN:0162-1459    

DOI:10.1080/01621459.1999.10474196

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

I introduce a class of Bayesian multiscale models (BMSM's) for one-dimensional inhomogeneous Poisson processes. The focus is on estimating the (discretized) intensity function underlying the process. Unlike the usual transform-based approach at the heart of most wavelet-based methods for Gaussian data, these BMSM's are constructed using recursive dyadic partitions (RDP's) within an entirely likelihood-based framework. Each RDP may be associated with a binary tree, and a new multiscale prior distribution is introduced for the unknown intensity through the placement of mixture distributions at each of the nodes of the tree. The concept of model mixing is then applied to a complete collection of such trees. In addition to allowing for the inclusion of full location/scale information in the model, this last step also is fundamental both in inducing stationarity in the prior distribution and in enabling a given intensity function to be approximated at the resolution of the data. Under squared-error loss, a closed-form recursive expression for the Bayes optimal estimator is derived, which makes computationally efficient implementation possible. The mixing parameters in the prior distribution can be interpreted as the “fraction of homogeneity” in the underlying intensity function at each scale, and I provide an empirical Bayes approach to eliciting their values, resulting in the ability to quantify multiscale structure in the data. The practical performance of the overall procedure is investigated through a series of simulations and illustrated using a real-data example from the field of high-energy astrophysics.

ISSN:0162-1459    

DOI:10.1080/01621459.1999.10474197

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

Over recent years, the use of homogeneous Gibbs prior models in image processing has become widely accepted. There has been, however, much discussion over precisely which models are most appropriate. For most applications, the simplest Gaussian model tends to oversmooth reconstructions, so it has been rejected in favor of various edge-preserving alternatives. We claim that the problem is not with the Gaussian family, but rather with the assumption of homogeneity. In this article we propose an inhomogeneous Gaussian random field as a general prior model for many image-processing applications. The simplicity of the Gaussian model allows rapid calculation, and the flexibility of the spatially varying prior parameter allows varying degrees of spatial smoothing. This approach is in the spirit of adaptive kernel density methods where only the choice of the variable window width is important. The analysis of real single-photon emission computed tomography data is used to illustrate the methods, and simulated data are used to demonstrate that the proposed procedures lead to more accurate reconstruction than edge-preserving homogeneous alternatives. The inhomogeneous model allows greater flexibility; small features are not masked by the smoothing, and constant regions obtain sufficient smoothing to remove the effects of noise.

ISSN:0162-1459    

DOI:10.1080/01621459.1999.10474198

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

In this article, we consider simultaneous outlier identification rules for multivariate data, generalizing the concept of so-calledαoutlier identifiers, as presented by Davies and Gather for the case of univariate samples. Such multivariate outlier identifiers are based on estimators of location and covariance. Therefore, it seems reasonable that characteristics of the estimators influence the behavior of outlier identifiers. Several authors mentioned that using estimators with low finite-sample breakdown point is not recommended for identifying outliers. To give a formal explanation, we investigate how the finite-sample breakdown points of estimators used in these identification rules influence the masking behavior of the rules.

ISSN:0162-1459    

DOI:10.1080/01621459.1999.10474199

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

The generalizedkmeans method is based on the minimization of the discrepancy between a random variable (or a sample of this random variable) and a set withkpoints measured through a penalty function Φ. As in theMestimators setting (k= 1), a penalty function, Φ, with unbounded derivative, Ψ, naturally leads to nonrobust generalizedkmeans. However, surprisingly the lack of robustness extends also to the case of bounded Ψ; that is, generalizedkmeans do not inherit the robustness properties of theMestimator from which they came. Attempting to robustify the generalizedkmeans method, the generalized trimmedkmeans method arises from combiningkmeans idea with a so-called impartial trimming procedure. In this article study generalizedkmeans and generalized trimmedkmeans performance from the viewpoint of Hampel's robustness criteria; that is, we investigate the influence function, breakdown point, and qualitative robustness, confirming the superiority provided by the trimming. We include the study of two real datasets to make clear the robustness of generalized trimmedkmeans.

ISSN:0162-1459    

DOI:10.1080/01621459.1999.10474200

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

We discuss two-armed clinical trials in which an ordinal response is observed on entry and at follow-up. In certain subject areas, such data are often reduced to the counts of patients who have deteriorated, remained the same, or improved. We develop asymptotic distribution theory to compare this approach to the use of nonparametric tests based on poststratification of the follow-up responses according to the entry levels. The theory for the latter approach is established by a general result for two-sampleUstatistics based on bivariate data. Application to data from clinical trials and evaluation of asymptotic relative efficiencies and powers for a variety of contexts illustrate the increased sensitivity of poststratified Wilcoxon tests.

ISSN:0162-1459    

DOI:10.1080/01621459.1999.10474201

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor

摘要:

Regression Graphics: Ideas for Studying Regression Through Graphics.R. Dennis Cook. New York: Wiley, 1998. ISBN 0-471-19365-8. xviii + 349 pp. $79.95 (H). Reviewed by Ker-Chau Li

ISSN:0162-1459    

DOI:10.1080/01621459.1999.10474202

出版商:Taylor & Francis Group    

年代:1999

数据来源: Taylor