Estimating overdispersion in sparse multinomial data.

abstract：:The Wilcoxon rank sum test is widely used for two-group comparisons for nonnormal data. An assumption of this test is independence of sampling units both between and within groups. In ophthalmology, data are often collected on two eyes of an individual, which are highly correlated. In ophthalmological clinical trials,...

journal_title：Biometrics

authors： Rosner B,Glynn RJ,Lee ML

更新日期：2006-12-01 00:00:00

abstract：:In this article, we present an estimation approach for solving nonlinear constrained generalized estimating equations that can be implemented using object-oriented software for nonlinear programming, such as nlminb in Splus or fmincon and lsqnonlin in Matlab. We show how standard estimating equation theory includes th...

journal_title：Biometrics

authors： Contreras M,Ryan LM

更新日期：2000-12-01 00:00:00

abstract：:We describe a simple, computationally efficient, permutation-based procedure for selecting the penalty parameter in LASSO-penalized regression. The procedure, permutation selection, is intended for applications where variable selection is the primary focus, and can be applied in a variety of structural settings, inclu...

journal_title：Biometrics

authors： Sabourin JA,Valdar W,Nobel AB

更新日期：2015-12-01 00:00:00

abstract：:For the case of repeated measures on Y with mean values linear in a concomitant variable Z in [a, b], a straight-line confidence band over [a, b] is given with width linear in Z. Graphical presentation of such line-segment confidence bands can help emphasize that appropriate inferences are limited to the range of the ...

journal_title：Biometrics

authors： Stewart PW

更新日期：1987-09-01 00:00:00

abstract：:Spatial weed count data are modeled and predicted using a generalized linear mixed model combined with a Bayesian approach and Markov chain Monte Carlo. Informative priors for a data set with sparse sampling are elicited using a previously collected data set with extensive sampling. Furthermore, we demonstrate that so...

journal_title：Biometrics

authors： Christensen OF,Waagepetersen R

更新日期：2002-06-01 00:00:00

abstract：:A method is proposed for calculating the probabilities of assignment of a patient to treatments; it involves minimizing a quadratic criterion subject to a balance constraint. The optimal probabilities are very easy to compute. Numerical illustration is given and comparisons are drawn with the entropy-based methods of ...

journal_title：Biometrics

authors： Titterington DM

更新日期：1983-12-01 00:00:00

abstract：:Five procedures are considered for the comparison of two or more multivariate samples. These procedures include a newly proposed nonparametric rank-sum test and a generalized least squares test. Also considered are the following tests: ordinary least squares, Hotelling's T2, and a Bonferroni per-experiment error-rate ...

journal_title：Biometrics

authors： O'Brien PC

更新日期：1984-12-01 00:00:00

abstract：:Identifying factors associated with increased medical cost is important for many micro- and macro-institutions, including the national economy and public health, insurers and the insured. However, assembling comprehensive national databases that include both the cost and individual-level predictors can prove challengi...

journal_title：Biometrics

authors： Johnson BA,Long Q,Huang Y,Chansky K,Redman M

更新日期：2016-09-01 00:00:00

abstract：:A class of adaptive weighted log-rank statistics is described where the vector of weights is chosen in a data-dependent way from a family of "smooth" weight vectors. A parametric family of weight vectors is identified which includes most shapes of weighting vectors that will be near optimal in many cancer prevention a...

journal_title：Biometrics

authors： Self SG

更新日期：1991-09-01 00:00:00

abstract：:Spatial data have become increasingly common in epidemiology and public health research thanks to advances in GIS (Geographic Information Systems) technology. In health research, for example, it is common for epidemiologists to incorporate geographically indexed data into their studies. In practice, however, the spati...

journal_title：Biometrics

authors： Huque MH,Bondell HD,Carroll RJ,Ryan LM

更新日期：2016-09-01 00:00:00

abstract：:A method is presented for choosing an additive constant c when transforming data x to y = log(x + c). The method preserves Type I error probability and power in ANOVA under the assumption that the x + c for some c are log-normally distributed. The method has advantages similar to those of rank transformations--namely,...

journal_title：Biometrics

authors： Berry DA

更新日期：1987-06-01 00:00:00

abstract：:We explore the use of a posterior predictive loss criterion for model selection for incomplete longitudinal data. We begin by identifying a property that most model selection criteria for incomplete data should consider. We then show that a straightforward extension of the Gelfand and Ghosh (1998, Biometrika, 85, 1-11...

journal_title：Biometrics

authors： Daniels MJ,Chatterjee AS,Wang C

更新日期：2012-12-01 00:00:00

abstract：:Prognostic models in survival analysis typically aim to describe the association between patient covariates and future outcomes. More recently, efforts have been made to include covariate information that is updated over time. However, there exists as yet no standard approach to assess the predictive accuracy of such ...

journal_title：Biometrics

authors： Schoop R,Graf E,Schumacher M

更新日期：2008-06-01 00:00:00

abstract：:Bayesian experimental design for a clinical trial involves specifying a utility function that models the purpose of the trial, in this case the selection of patients for a diagnostic test. The best sample of patients is selected by maximizing expected utility. This optimization task poses difficulties due to a high-di...

journal_title：Biometrics

authors： Buzoianu M,Kadane JB

更新日期：2009-09-01 00:00:00

abstract：:The objective of this article is to develop a hypothesis-testing procedure to determine whether a common source outbreak has ended. We consider the case when neither the calendar date of exposure to the pathogen nor the exact incubation period distribution is known. The hypothesis-testing procedure is based on the spa...

journal_title：Biometrics

authors： Brookmeyer R,You X

更新日期：2006-03-01 00:00:00

abstract：:Brain connectivity analysis is now at the foreground of neuroscience research. A connectivity network is characterized by a graph, where nodes represent neural elements such as neurons and brain regions, and links represent statistical dependence that is often encoded in terms of partial correlation. Such a graph is i...

journal_title：Biometrics

authors： Xia Y,Li L

更新日期：2017-09-01 00:00:00

abstract：SUMMARY:A trend test is often employed to analyze ordered categorical data, in which a set of increasing scores is assigned a priori. There is a drawback in this approach, because how to choose a set of scores is not clear. There have been debates on which scores should be used (e.g., Graubard and Korn, 1987, Biometric...

journal_title：Biometrics

authors： Zheng G

更新日期：2008-12-01 00:00:00

abstract：:In this article, we propose approximate sample size formulas for establishing equivalence or noninferiority of two treatments in match-pairs design. Using the ratio of two proportions as the equivalence measure, we derive sample size formulas based on a score statistic for two types of analyses: hypothesis testing and...

journal_title：Biometrics

authors： Tang ML,Tang NS,Chan IS,Chan BP

更新日期：2002-12-01 00:00:00

abstract：:Stepped wedge designed trials are a type of cluster-randomized study in which the intervention is introduced to each cluster in a random order over time. This design is often used to assess the effect of a new intervention as it is rolled out across a series of clinics or communities. Based on a permutation argument, ...

journal_title：Biometrics

authors： Hughes JP,Heagerty PJ,Xia F,Ren Y

更新日期：2020-03-01 00:00:00

abstract：:Image-on-image regression analysis, using images to predict images, is a challenging task, due to (1) the high dimensionality and (2) the complex spatial dependence structures in image predictors and image outcomes. In this work, we propose a novel image-on-image regression model, by extending a spatial Bayesian laten...

journal_title：Biometrics

authors： Guo C,Kang J,Johnson TD

更新日期：2020-12-27 00:00:00

abstract：:We consider methods for estimating the treatment effect and/or the covariate by treatment interaction effect in a randomized clinical trial under noncompliance with time-to-event outcome. As in Cuzick et al. (2007), assuming that the patient population consists of three (possibly latent) subgroups based on treatment p...

journal_title：Biometrics

authors： Li S,Gray RJ

更新日期：2016-09-01 00:00:00

abstract：:A transformed Bernstein polynomial that is centered at standard parametric families, such as Weibull or log-logistic, is proposed for use in the accelerated hazards model. This class provides a convenient way towards creating a Bayesian nonparametric prior for smooth densities, blending the merits of parametric and no...

journal_title：Biometrics

authors： Chen Y,Hanson T,Zhang J

更新日期：2014-03-01 00:00:00

abstract：:Restricted maximum likelihood (REML) is now well established as a method for estimating the parameters of the general Gaussian linear model with a structured covariance matrix, in particular for mixed linear models. Conventionally, estimates of precision and inference for fixed effects are based on their asymptotic di...

journal_title：Biometrics

authors： Kenward MG,Roger JH

更新日期：1997-09-01 00:00:00

abstract：:In the context of group testing screening, McMahan, Tebbs, and Bilder (2012, Biometrics 68, 287-296) proposed a two-stage procedure in a heterogenous population in the presence of misclassification. In earlier work published in Biometrics, Kim, Hudgens, Dreyfuss, Westreich, and Pilcher (2007, Biometrics 63, 1152-1162)...

journal_title：Biometrics

authors： Malinovsky Y,Albert PS,Roy A

更新日期：2016-03-01 00:00:00

abstract：:There has been great interest in developing nonlinear structural equation models and associated statistical inference procedures, including estimation and model selection methods. In this paper a general semiparametric structural equation model (SSEM) is developed in which the structural equation is composed of nonpar...

journal_title：Biometrics

authors： Guo R,Zhu H,Chow SM,Ibrahim JG

更新日期：2012-06-01 00:00:00

abstract：:Multivariate current status data, consist of indicators of whether each of several events occur by the time of a single examination. Our interest focuses on inferences about the joint distribution of the event times. Conventional methods for analysis of multiple event-time data cannot be used because all of the event ...

journal_title：Biometrics

authors： Dunson DB,Dinse GE

更新日期：2002-03-01 00:00:00

abstract：:We propose a response-adaptive model for functional linear regression, which is adapted to sparsely sampled longitudinal responses. Our method aims at predicting response trajectories and models the regression relationship by directly conditioning the sparse and irregular observations of the response on the predictor,...

journal_title：Biometrics

authors： Wu S,Müller HG

更新日期：2011-09-01 00:00:00

abstract：:Some covariate-adaptive randomization methods have been used in clinical trials for a long time, but little theoretical work has been done about testing hypotheses under covariate-adaptive randomization until Shao et al. (2010) who provided a theory with detailed discussion for responses under linear models. In this a...

journal_title：Biometrics

authors： Shao J,Yu X

更新日期：2013-12-01 00:00:00

abstract：:In multivariate survival analysis, investigators are often interested in testing for heterogeneity among clusters, both overall and within specific classes. We represent different hypotheses about the heterogeneity structure using a sequence of gamma frailty models, ranging from a null model with no random effects to ...

journal_title：Biometrics

authors： Dunson DB,Chen Z

更新日期：2004-06-01 00:00:00

abstract：SUMMARY:In this article we investigate regression calibration methods to jointly model longitudinal and survival data using a semiparametric longitudinal model and a proportional hazards model. In the longitudinal model, a biomarker is assumed to follow a semiparametric mixed model where covariate effects are modeled p...

journal_title：Biometrics

authors： Ye W,Lin X,Taylor JM

更新日期：2008-12-01 00:00:00