American Statistician最新文献_第10页

P-Value Precision and Reproducibility. p值精密度和再现性。

IF 1.8 4区数学

American Statistician Pub Date : 2011-01-01 Epub Date: 2012-01-24 DOI: 10.1198/tas.2011.10129

Dennis D Boos, Leonard A Stefanski

引用次数: 178

A Note on Comparing the Power of Test Statistics at Low Significance Levels. 关于在低显著性水平下比较检验统计量的能力的注释。

IF 1.8 4区数学

American Statistician Pub Date : 2011-01-01 DOI: 10.1198/tast.2011.10117

Nathan Morris, Robert Elston

引用次数: 9

Consistency of Normal Distribution Based Pseudo Maximum Likelihood Estimates When Data Are Missing at Random. 数据随机缺失时基于正态分布的伪极大似然估计的一致性。

IF 1.8 4区数学

American Statistician Pub Date : 2010-08-01 DOI: 10.1198/tast.2010.09203

Ke-Hai Yuan, Peter M Bentler

引用次数: 15

Non-linear Models for Longitudinal Data. 纵向数据的非线性模型。

IF 1.8 4区数学

American Statistician Pub Date : 2009-11-01 DOI: 10.1198/tast.2009.07256

Jan Serroyen, Geert Molenberghs, Geert Verbeke, Marie Davidian

引用次数: 34

Rating Movies and Rating the Raters Who Rate Them. 给电影打分，给给电影打分的人打分。

IF 1.8 4区数学

American Statistician Pub Date : 2009-11-01 DOI: 10.1198/tast.2009.08278

Hua Zhou, Kenneth Lange

{"title":"Rating Movies and Rating the Raters Who Rate Them.","authors":"Hua Zhou, Kenneth Lange","doi":"10.1198/tast.2009.08278","DOIUrl":"https://doi.org/10.1198/tast.2009.08278","url":null,"abstract":"The movie distribution company Netflix has generated considerable buzz in the statistics community by offering a million dollar prize for improvements to its movie rating system. Among the statisticians and computer scientists who have disclosed their techniques, the emphasis has been on machine learning approaches. This article has the modest goal of discussing a simple model for movie rating and other forms of democratic rating. Because the model involves a large number of parameters, it is nontrivial to carry out maximum likelihood estimation. Here we derive a straightforward EM algorithm from the perspective of the more general MM algorithm. The algorithm is capable of finding the global maximum on a likelihood landscape littered with inferior modes. We apply two variants of the model to a dataset from the MovieLens archive and compare their results. Our model identifies quirky raters, redefines the raw rankings, and permits imputation of missing ratings. The model is intended to stimulate discussion and development of better theory rather than to win the prize. It has the added benefit of introducing readers to some of the issues connected with analyzing high-dimensional data.","PeriodicalId":50801,"journal":{"name":"American Statistician","volume":"63 4","pages":"297-307"},"PeriodicalIF":1.8,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1198/tast.2009.08278","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29274882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 20

Easy Multiplicity Control in Equivalence Testing Using Two One-sided Tests. 使用两个单侧检验的等价检验中的简单多重控制。

IF 1.8 4区数学

American Statistician Pub Date : 2009-05-01 DOI: 10.1198/tast.2009.0029

Carolyn Lauzon, Brian Caffo

引用次数: 45

On the Assessment of Monte Carlo Error in Simulation-Based Statistical Analyses. 基于仿真的统计分析中蒙特卡罗误差的评定。

IF 1.8 4区数学

American Statistician Pub Date : 2009-05-01 DOI: 10.1198/tast.2009.0030

Elizabeth Koehler, Elizabeth Brown, Sebastien J-P A Haneuse

{"title":"On the Assessment of Monte Carlo Error in Simulation-Based Statistical Analyses.","authors":"Elizabeth Koehler, Elizabeth Brown, Sebastien J-P A Haneuse","doi":"10.1198/tast.2009.0030","DOIUrl":"https://doi.org/10.1198/tast.2009.0030","url":null,"abstract":"Statistical experiments, more commonly referred to as Monte Carlo or simulation studies, are used to study the behavior of statistical methods and measures under controlled situations. Whereas recent computing and methodological advances have permitted increased efficiency in the simulation process, known as variance reduction, such experiments remain limited by their finite nature and hence are subject to uncertainty; when a simulation is run more than once, different results are obtained. However, virtually no emphasis has been placed on reporting the uncertainty, referred to here as Monte Carlo error, associated with simulation results in the published literature, or on justifying the number of replications used. These deserve broader consideration. Here we present a series of simple and practical methods for estimating Monte Carlo error as well as determining the number of replications required to achieve a desired level of accuracy. The issues and methods are demonstrated with two simple examples, one evaluating operating characteristics of the maximum likelihood estimator for the parameters in logistic regression and the other in the context of using the bootstrap to obtain 95% confidence intervals. The results suggest that in many settings, Monte Carlo error may be more substantial than traditionally thought.","PeriodicalId":50801,"journal":{"name":"American Statistician","volume":" ","pages":"155-162"},"PeriodicalIF":1.8,"publicationDate":"2009-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1198/tast.2009.0030","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40192743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 244

A Fresh Look at the Discriminant Function Approach for Estimating Crude or Adjusted Odds Ratios. 重新审视用于估算粗略或调整比值比的判别函数方法。

IF 1.8 4区数学

American Statistician Pub Date : 2009-01-01 DOI: 10.1198/tast.2009.08246

Robert H Lyles, Ying Guo, Andrew N Hill

{"title":"A Fresh Look at the Discriminant Function Approach for Estimating Crude or Adjusted Odds Ratios.","authors":"Robert H Lyles, Ying Guo, Andrew N Hill","doi":"10.1198/tast.2009.08246","DOIUrl":"10.1198/tast.2009.08246","url":null,"abstract":"Assuming a binary outcome, logistic regression is the most common approach to estimating a crude or adjusted odds ratio corresponding to a continuous predictor. We revisit a method termed the discriminant function approach, which leads to closed-form estimators and corresponding standard errors. In its most appealing application, we show that the approach suggests a multiple linear regression of the continuous predictor of interest on the outcome and other covariates, in place of the traditional logistic regression model. If standard diagnostics support the assumptions (including normality of errors) accompanying this linear regression model, the resulting estimator has demonstrable advantages over the usual maximum likelihood estimator via logistic regression. These include improvements in terms of bias and efficiency based on a minimum variance unbiased estimator of the log odds ratio, as well as the availability of an estimate when logistic regression fails to converge due to a separation of data points. Use of the discriminant function approach as described here for multivariable analysis requires less stringent assumptions than those for which it was historically criticized, and is worth considering when the adjusted odds ratio associated with a particular continuous predictor is of primary interest. Simulation and case studies illustrate these points.","PeriodicalId":50801,"journal":{"name":"American Statistician","volume":"63 4","pages":""},"PeriodicalIF":1.8,"publicationDate":"2009-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3881534/pdf/nihms536814.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32012162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Flexible Frames and Control Sampling in Case-Control Studies: Weighters (Survey Statisticians) Versus Anti-Weighters (Epidemiologists). 病例对照研究中的灵活框架和对照抽样:权重者(调查统计学家)与反权重者(流行病学家)。

IF 1.8 4区数学

American Statistician Pub Date : 2008-11-01 DOI: 10.1198/000313008X364525

Richard F Potthoff, Susan Halabi, Joellen M Schildkraut, Beth Newman

引用次数: 5

Linear Transformations and the k-Means Clustering Algorithm: Applications to Clustering Curves. 线性变换和k-均值聚类算法:聚类曲线的应用。

IF 1.8 4区数学

American Statistician Pub Date : 2007-02-01 DOI: 10.1198/000313007X171016

Thaddeus Tarpey

引用次数: 85