Journal of the American Statistical Association

最新文章

• Estimating a unimodal distribution from interval-censored data AI翻译
  作者：Duembgen, Lutz; Freitag-Wolf, Sandra; Jongbloed, Geurt
  作者单位：University of Bern; University of Kiel; Vrije Universiteit Amsterdam
  摘要：In this article we consider three nonparametric maximum likelihood estimators based on mixed-case interval-censored data. Apart from the unrestricted estimator, we consider estimators under the assumption that the underlying distribution function of event times is concave or unimodal. Characterizations of the estimates are derived, and algorithms are proposed for their computation. The estimators are shown to be asymptotically consistent, and the benefits of additional constraints are illustra...
• Hidden Markov models for microarray time course data in multiple biological conditions AI翻译
  作者：Yuan, Ming; Kendziorski, Christina
  作者单位：University System of Georgia; Georgia Institute of Technology; University of Wisconsin System; University of Wisconsin Madison
  摘要：Among the first microarray experiments were those measuring expression over time, and time course experiments remain common. Most methods to analyze time course data attempt to group genes sharing similar temporal profiles within a single biological condition. However. with time course data in multiple conditions, a main goal is to identify differential expression patterns over time. An intuitive approach to this problem would be to apply at each time point any of the many methods for identify...
• A constructive representation of univariate skewed distributions AI翻译
  作者：Ferreira, Jose T. A. S.; Steel, Mark F. J.
  作者单位：University of Warwick
  摘要：We introduce a general perspective on the introduction of skewness into symmetric distributions. Through inverse probability integral transformations we provide a constructive representation of skewed distributions, where the skewing mechanism and the original symmetric distributions are specified separately. We study the effects of the skewing mechanism on, e.g., modality, tail behavior and the amount of skewness generated. The representation is used to introduce novel classes of skewed distr...
• Order-based dependent Dirichlet processes AI翻译
  作者：Griffin, JE; Steel, MFJ
  作者单位：University of Warwick
  摘要：In this article we propose a new framework for Bayesian nonparametric modeling with continuous covariates. In particular. we allow the nonparametric distribution to depend on covariates through ordering the random variables building the weights in the stick-breaking representation. We focus mostly on the class of random distributions that induces a Dirichlet process at each covariate value. We derive the correlation between distributions at different covariate values and use a point process to...
• Bayesian inference for a two-part hierarchical model: An application to profiling providers in managed health care AI翻译
  作者：Zhang, Min; Strawderman, Robert L.; Cowen, Mark E.; T Wells, Martin
  作者单位：Purdue University System; Purdue University; Cornell University; Saint Joseph Mercy Health System (SJMHS)
  摘要：Profiling is currently an important, and hotly debated, topic in health care and other industries looking for ways to control costs, increase profitability, and increase service quality. Managed care in particular has seen a proliferation in the use of statistical profiling methodology, particularly with regard to monitoring expenditure data. This article focuses on the specific problem of developing statistical methods appropriate for profiling physician contributions to patient pharmacy expe...
• Incorporating additional information to normal linear discriminant rules AI翻译
  作者：Fernandez, Miguel A.; Rueda, Cristina; Salvador, Bonifacio
  作者单位：Universidad de Valladolid
  摘要：The most useful and broadly known rule in the classical two-group linear normal discriminant analysis is Anderson's rule. In this article we propose some alternative procedures that prove useful when prior constraints on the mean vectors are known. These rules are based on new estimators of the difference of means. We prove under mild conditions that the new rules perform better when the common covariance matrix is known. Simulated experiments show that the misclassification errors are lower f...
• On δ-equivalence with the best in k-sample models AI翻译
  作者：Finner, H.; Strassburger, K.
  作者单位：Heinrich Heine University Dusseldorf; Leibniz Association; Deutsches Diabetes-Zentrum (DDZ)
  摘要：In recent work we introduced a general, a weak, and a strong partitioning principles for the construction of multiple decision procedures as multiple testing or selection procedures. Partitioning principles can be viewed as natural extensions of the closure principle and sometimes yield more powerful decision procedures. In this article we consider the problem of establishing equivalence with the best with respect to k treatment means, where equivalence is defined in terms of a threshold value...
• Testing for covariate effects in the fully nonparametric analysis of covariance model AI翻译
  作者：Wang, Lan; Akritas, Michael G.
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
  摘要：Traditional inference questions in the analysis of covariance mainly focus on comparing different factor levels by adjusting for the continuous covariates, which are believed to also exert a significant effect on the outcome variable. Testing hypotheses about the covariate effects, although of substantial interest in many applications, has received relatively limited study in the semiparametric/nonparametric setting. In the context of the fully nonparametric analysis of covariance model of Akr...
• A distributional approach for causal inference using propensity scores AI翻译
  作者：Tan, Zhiqiang
  作者单位：Johns Hopkins University; Johns Hopkins Bloomberg School of Public Health
  摘要：Drawing inferences about the effects of treatments and actions is a common challenge in economics, epidemiology, and other fields. We adopt Rubin's potential outcomes framework for causal inference and propose two methods serving complementary purposes. One can be used to estimate average causal effects, assuming no confounding given measured covariates. The other can be used to assess how the estimates might change under various departures from no confounding. Both methods are developed from ...
• Geoadditive survival models AI翻译
  作者：Hennerfeind, Andrea; Brezger, Andreas; Fahrmeir, Ludwig
  作者单位：University of Munich
  摘要：Survival data often contain small-area geographical or spatial information, such as the residence of individuals. In many cases, the impact of such spatial effects on hazard rates is of considerable substantive interest. Therefore, extensions of known survival or hazard rate models to spatial models have been suggested. Mostly, a spatial component is added to the usual linear predictor of the Cox model. In this article flexible continuous-time geoaddifive models are proposed, extending the Cox...