Pub Date : 2024-06-17DOI: 10.1080/00031305.2024.2368794
Mohammad Ehsanul Karim
“The use of health care claims datasets often encounters criticism due to the pervasive issues of omitted variables and inaccuracies or mis-measurements in available confounders. Ultimately, the tr...
{"title":"High-dimensional propensity score and its machine learning extensions in residual confounding control","authors":"Mohammad Ehsanul Karim","doi":"10.1080/00031305.2024.2368794","DOIUrl":"https://doi.org/10.1080/00031305.2024.2368794","url":null,"abstract":"“The use of health care claims datasets often encounters criticism due to the pervasive issues of omitted variables and inaccuracies or mis-measurements in available confounders. Ultimately, the tr...","PeriodicalId":50801,"journal":{"name":"American Statistician","volume":"51 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141436061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-17DOI: 10.1080/00031305.2024.2368799
Jia Liang, Shuo Chen, Peter Kochunov, L. Elliot Hong, Chixiang Chen
A full parametric and linear specification may be insufficient to capture complicated patterns in studies exploring complex features, such as those investigating age-related changes in brain functi...
{"title":"Integrative data analysis where partial covariates have complex non-linear effects by using summary information from an external data","authors":"Jia Liang, Shuo Chen, Peter Kochunov, L. Elliot Hong, Chixiang Chen","doi":"10.1080/00031305.2024.2368799","DOIUrl":"https://doi.org/10.1080/00031305.2024.2368799","url":null,"abstract":"A full parametric and linear specification may be insufficient to capture complicated patterns in studies exploring complex features, such as those investigating age-related changes in brain functi...","PeriodicalId":50801,"journal":{"name":"American Statistician","volume":"16 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141425530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-07DOI: 10.1080/00031305.2024.2365673
Nicholas Clark, Christopher Morrell, Mike Powell
In recent years, there has been an explosion in the growth of undergraduate statistics and data science programs across the US. Simultaneously, there has been clear guidance written on curriculum d...
{"title":"Assessment and Continuous Improvement of an Undergraduate Data Science Program","authors":"Nicholas Clark, Christopher Morrell, Mike Powell","doi":"10.1080/00031305.2024.2365673","DOIUrl":"https://doi.org/10.1080/00031305.2024.2365673","url":null,"abstract":"In recent years, there has been an explosion in the growth of undergraduate statistics and data science programs across the US. Simultaneously, there has been clear guidance written on curriculum d...","PeriodicalId":50801,"journal":{"name":"American Statistician","volume":"5 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141326824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-28DOI: 10.1080/00031305.2024.2356109
Jonathan J. Chipman, Robert A. Greevy Jr., Lindsay Mayberry, Jeffrey D. Blume
The Second Generation P-Value (SGPV) measures the overlap between an estimated interval and a composite hypothesis of parameter values. We develop a sequential monitoring scheme of the SGPV (SeqSGP...
第二代 P 值（SGPV）测量估计区间与参数值复合假设之间的重叠程度。我们开发了一种 SGPV 的顺序监测方案（SeqSGP...
{"title":"Sequential monitoring using the Second Generation P-Value with Type I error controlled by monitoring frequency","authors":"Jonathan J. Chipman, Robert A. Greevy Jr., Lindsay Mayberry, Jeffrey D. Blume","doi":"10.1080/00031305.2024.2356109","DOIUrl":"https://doi.org/10.1080/00031305.2024.2356109","url":null,"abstract":"The Second Generation P-Value (SGPV) measures the overlap between an estimated interval and a composite hypothesis of parameter values. We develop a sequential monitoring scheme of the SGPV (SeqSGP...","PeriodicalId":50801,"journal":{"name":"American Statistician","volume":"61 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141159781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-09DOI: 10.1080/00031305.2024.2352010
Eric Yanchenko, Howard D. Bondell, Brian J. Reich
In Bayesian analysis, the selection of a prior distribution is typically done by considering each parameter in the model. While this can be convenient, in many scenarios it may be desirable to plac...
{"title":"The R2D2 prior for generalized linear mixed models","authors":"Eric Yanchenko, Howard D. Bondell, Brian J. Reich","doi":"10.1080/00031305.2024.2352010","DOIUrl":"https://doi.org/10.1080/00031305.2024.2352010","url":null,"abstract":"In Bayesian analysis, the selection of a prior distribution is typically done by considering each parameter in the model. While this can be convenient, in many scenarios it may be desirable to plac...","PeriodicalId":50801,"journal":{"name":"American Statistician","volume":"37 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140914946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-07DOI: 10.1080/00031305.2024.2351999
Christopher M. Rump
The best time to play the lottery is when the jackpot has rolled over several times and grown large, but not so large that you must share the prize if you win. We examine maximizing the expected va...
{"title":"The Best Time to Play the Lottery","authors":"Christopher M. Rump","doi":"10.1080/00031305.2024.2351999","DOIUrl":"https://doi.org/10.1080/00031305.2024.2351999","url":null,"abstract":"The best time to play the lottery is when the jackpot has rolled over several times and grown large, but not so large that you must share the prize if you win. We examine maximizing the expected va...","PeriodicalId":50801,"journal":{"name":"American Statistician","volume":"14 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140907424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-02DOI: 10.1080/00031305.2024.2350449
Niels G. Waller
This article describes a simple and fast algorithm for generating correlation matrices ( R) with a known average correlation. The algorithm should be useful for researchers desiring plausible R m...
本文介绍了一种简单快速的算法，用于生成具有已知平均相关性的相关矩阵 ( R)。该算法对于希望获得可信的 R 矩阵的研究人员来说非常有用。
{"title":"A Simple and Fast Algorithm for Generating Correlation Matrices with a Known Average Correlation Coefficient","authors":"Niels G. Waller","doi":"10.1080/00031305.2024.2350449","DOIUrl":"https://doi.org/10.1080/00031305.2024.2350449","url":null,"abstract":"This article describes a simple and fast algorithm for generating correlation matrices ( R) with a known average correlation. The algorithm should be useful for researchers desiring plausible R m...","PeriodicalId":50801,"journal":{"name":"American Statistician","volume":"2014 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140914888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-02DOI: 10.1080/00031305.2024.2350445
Owen McGrath, Kevin Burke
Confidence interval performance is typically assessed in terms of two criteria: coverage probability and interval width (or margin of error). In this paper, we assess the performance of four common...
{"title":"Binomial Confidence Intervals for Rare Events: Importance of Defining Margin of Error Relative to Magnitude of Proportion","authors":"Owen McGrath, Kevin Burke","doi":"10.1080/00031305.2024.2350445","DOIUrl":"https://doi.org/10.1080/00031305.2024.2350445","url":null,"abstract":"Confidence interval performance is typically assessed in terms of two criteria: coverage probability and interval width (or margin of error). In this paper, we assess the performance of four common...","PeriodicalId":50801,"journal":{"name":"American Statistician","volume":"43 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140915034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-02DOI: 10.1080/00031305.2024.2350452
Marc Aerts, Geert Molenberghs
Squared 2 × 2 tables with binary data from matched pairs are typically analysed using Cochran-Mantel-Haenszel methodology, conditional logistic regression, or random intercepts logistic regression....
{"title":"Analyzing Matched 2 × 2 Tables from all Corners","authors":"Marc Aerts, Geert Molenberghs","doi":"10.1080/00031305.2024.2350452","DOIUrl":"https://doi.org/10.1080/00031305.2024.2350452","url":null,"abstract":"Squared 2 × 2 tables with binary data from matched pairs are typically analysed using Cochran-Mantel-Haenszel methodology, conditional logistic regression, or random intercepts logistic regression....","PeriodicalId":50801,"journal":{"name":"American Statistician","volume":"425 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140907405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-23DOI: 10.1080/00031305.2024.2339562
Piotr Fryzlewicz
Published in The American Statistician (Ahead of Print, 2024)
发表于《美国统计学家》（2024 年提前出版）
{"title":"Telling Stories with Data: With Applications in R","authors":"Piotr Fryzlewicz","doi":"10.1080/00031305.2024.2339562","DOIUrl":"https://doi.org/10.1080/00031305.2024.2339562","url":null,"abstract":"Published in The American Statistician (Ahead of Print, 2024)","PeriodicalId":50801,"journal":{"name":"American Statistician","volume":"105 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140648749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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