发布求助
文献互助 智能选刊 最新文献

Observational studies最新文献

筛选
英文 中文
Nonparametric Bayes: A Bridge Between Cultures 非参数贝叶斯：文化之间的桥梁
Observational studies Pub Date : 2021-07-27 DOI: 10.1353/obs.2021.0005
Arman Oganisian, J. Roy
{"title":"Nonparametric Bayes: A Bridge Between Cultures","authors":"Arman Oganisian, J. Roy","doi":"10.1353/obs.2021.0005","DOIUrl":"https://doi.org/10.1353/obs.2021.0005","url":null,"abstract":"Abstract:In this commentary, we assess the cultural fit of Bayesian nonparametrics in light of advances in the field since Breiman's 2001 article. We argue that Bayesian nonparametrics synthesizes desirable elements of the data modeling and algorithmic cultures to yield new insights and methodological improvements. We discuss how these methods have been combined with identification strategies from the causal inference literature to do flexible inference for interpretable target parameters.","PeriodicalId":74335,"journal":{"name":"Observational studies","volume":"7 1","pages":"175 - 178"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46892734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Leo Breiman's Challenge: A Retrospective Leo Breiman的挑战:回顾
Observational studies Pub Date : 2021-07-27 DOI: 10.1353/obs.2021.0017
D. Banks
{"title":"Leo Breiman's Challenge: A Retrospective","authors":"D. Banks","doi":"10.1353/obs.2021.0017","DOIUrl":"https://doi.org/10.1353/obs.2021.0017","url":null,"abstract":"Abstract:Breiman led the way in thinking differently about statistics. Many of his iconoclastic ideas have become standard in the data science sphere. This discussion argues for some rebalancing, while gratefully acknowledging his achievements.","PeriodicalId":74335,"journal":{"name":"Observational studies","volume":"7 1","pages":"13 - 15"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1353/obs.2021.0017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66461065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Causally Colored Reflections on Leo Breiman's "Statistical Modeling: The Two Cultures" (2001) 对Leo Breiman“统计建模：两种文化”（2001）的因果有色思考
Observational studies Pub Date : 2021-07-27 DOI: 10.1353/obs.2021.0008
J. Pearl
{"title":"Causally Colored Reflections on Leo Breiman's \"Statistical Modeling: The Two Cultures\" (2001)","authors":"J. Pearl","doi":"10.1353/obs.2021.0008","DOIUrl":"https://doi.org/10.1353/obs.2021.0008","url":null,"abstract":"Abstract:This note provides a re-assessment of Breiman's contributions to the art of statistical modeling, in light of recent advances in machine learning and causal inference. It highlights the crisp separation between the data-fitting and data-interpretation components of statistical modeling.","PeriodicalId":74335,"journal":{"name":"Observational studies","volume":"7 1","pages":"187 - 190"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1353/obs.2021.0008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46247573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Reasoning Using Data: Two Old Ways and One New 数据推理:两种旧方法和一种新方法
Observational studies Pub Date : 2021-07-27 DOI: 10.1353/obs.2021.0016
M. Baiocchi, J. Rodu
{"title":"Reasoning Using Data: Two Old Ways and One New","authors":"M. Baiocchi, J. Rodu","doi":"10.1353/obs.2021.0016","DOIUrl":"https://doi.org/10.1353/obs.2021.0016","url":null,"abstract":"Abstract:Instead of two cultures, the story of the last couple decades of data science is about the interplay between three different types of reasoning using data. Two of these types of reasoning were well known when Breiman wrote his Two Cultures paper – warranted reasoning (e.g., randomized trials and sampling) and model reasoning (e.g., linear models). Breiman, though he does not appear to have realized it fully, was in fact describing the dynamics arising in a data community that was making progress using the newest, third type of reasoning – outcome reasoning. In this commentary we clarify this dynamic a bit, and suggest some useful language for identifying and differentiating types of problems better suited for outcome reasoning.","PeriodicalId":74335,"journal":{"name":"Observational studies","volume":"7 1","pages":"12 - 3"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45242994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Statistical Modelling in the Age of Data Science 数据科学时代的统计建模
Observational studies Pub Date : 2021-07-27 DOI: 10.1353/obs.2021.0013
S. Vansteelandt
{"title":"Statistical Modelling in the Age of Data Science","authors":"S. Vansteelandt","doi":"10.1353/obs.2021.0013","DOIUrl":"https://doi.org/10.1353/obs.2021.0013","url":null,"abstract":"Abstract:Twenty years after Leo Breiman's wake-up call on the use of data models, I reconsider his concerns, which were heavily influenced by problems in prediction and classification, in light of the much vaster class of problems of estimating effects and (conditional) associations. Viewed from this perspective, one realises that the statistical community's commitment to the use of data models continues to be dominant and problematic, but that algorithmic modelling (machine learning) does not readily provide a satisfactory alternative, by virtue of being almost exclusively focused on prediction and classification. The only successful way forward is to bridge the two cultures. It requires machine learning skills from the algorithmic modelling culture in order to reduce model misspecification bias and to enable pre-specification of the statistical analysis. It moreover requires data modelling skills in order to choose and construct interpretable effect and association measures that target the scientific question; in order to identify those measures from observed data under the considered sampling design by relating to minimal and well-understood assumptions; and finally, in order to reduce regularisation bias and quantify uncertainty in the obtained estimates by relating to asymptotic theory.","PeriodicalId":74335,"journal":{"name":"Observational studies","volume":"7 1","pages":"217 - 228"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44767646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Modern Data Modeling: Cross-Fertilization of the Two Cultures 现代数据建模:两种文化的交叉受精
Observational studies Pub Date : 2021-07-27 DOI: 10.1353/obs.2021.0023
Jianqing Fan, Cong Ma, Kaizheng Wang, Ziwei Zhu
{"title":"Modern Data Modeling: Cross-Fertilization of the Two Cultures","authors":"Jianqing Fan, Cong Ma, Kaizheng Wang, Ziwei Zhu","doi":"10.1353/obs.2021.0023","DOIUrl":"https://doi.org/10.1353/obs.2021.0023","url":null,"abstract":"Abstract:The past two decades have witnessed deep cross-fertilization between the two cultures—statistics (data/generative modeling) and machine learning (algorithmic modeling), which is in stark contrast to the scene pictured in Breiman's inspiring work. In light of this major confluence, we find it helpful to single out a few salient examples showcasing the impacts of one to the other, and the research progress out of them. We point out in the end that the current big data era especially requires joint efforts from both cultures in order to address some common challenges including decentralized data analysis, privacy, fairness, etc.","PeriodicalId":74335,"journal":{"name":"Observational studies","volume":"7 1","pages":"65 - 76"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44653723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
The Two Cultures: Statistics and Machine Learning in Science 两种文化：科学中的统计学和机器学习
Observational studies Pub Date : 2021-07-27 DOI: 10.1353/obs.2021.0000
R. Kass
{"title":"The Two Cultures: Statistics and Machine Learning in Science","authors":"R. Kass","doi":"10.1353/obs.2021.0000","DOIUrl":"https://doi.org/10.1353/obs.2021.0000","url":null,"abstract":"Abstract:In his 2001 Statistical Science paper, Leo Breiman called attention to \"two cultures\" of data analysts, the first associated with computer science and the second with statistics. Breiman saw flaws in the traditionally-oriented statistical culture and advocated the predictively-oriented approach he identified with computer science. Although many of his observations were accurate and useful, Breiman failed to acknowledge the merits of statistical modeling, and he mischaracterized the role of statistics in science. To explain, I discuss machine learning and artificial intelligence; excessive cautiousness in statistics; dangers of statistical modeling; potential accomplishments of statistical modeling; the statistical paradigm; the nature of statistical models; and statistical methods that work well in practice. Everyone who is interested in the use of computer science and statistics in data analysis should grapple with the issues raised by Breiman's article.","PeriodicalId":74335,"journal":{"name":"Observational studies","volume":"7 1","pages":"135 - 144"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46545125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Comment on Breiman's "Two Cultures" (2002): From Two Cultures to Multicultural 评布莱曼的“两种文化”（2002）：从两种文化到多元文化
Observational studies Pub Date : 2021-07-27 DOI: 10.1353/obs.2021.0010
G. Shmueli
{"title":"Comment on Breiman's \"Two Cultures\" (2002): From Two Cultures to Multicultural","authors":"G. Shmueli","doi":"10.1353/obs.2021.0010","DOIUrl":"https://doi.org/10.1353/obs.2021.0010","url":null,"abstract":"Abstract:Since Breiman's \"Two Cultures\" paper's appearance in 2002, the term prediction has gained incredible significance in research, practice, society, and humanity. \"Two Cultures\" led to many useful advancements and surprising discoveries. Experiencing first hand the different cultures in the statistics and machine learning communities that Brieman expressed so early and clearly, I've then encountered even more differences. I describe additional modeling distinctions and further modeling \"cultures\". Recognizing these cultures, understanding their reasoning, and comparing and contrasting them, opens our eyes to new ways of viewing the world and creates opportunities for innovation and collaboration.","PeriodicalId":74335,"journal":{"name":"Observational studies","volume":"7 1","pages":"197 - 201"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45798487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Discussion of Breiman's "Two Cultures": From Two Cultures to One 论布莱曼的“两种文化”：从两种文化到一种文化
Observational studies Pub Date : 2021-07-27 DOI: 10.1353/obs.2021.0004
Anna Neufeld, D. Witten
{"title":"Discussion of Breiman's \"Two Cultures\": From Two Cultures to One","authors":"Anna Neufeld, D. Witten","doi":"10.1353/obs.2021.0004","DOIUrl":"https://doi.org/10.1353/obs.2021.0004","url":null,"abstract":"Abstract:We argue that algorithmic models, though powerful and appropriate in some circumstances, rely on just as many tenuous assumptions as parametric probabilistic models; these assumptions, their violations, and the ethical consequences of these violations are simply obscured within a black box. We advocate for a future in which statisticians play a central role in bridging the gap between Breiman's two cultures.","PeriodicalId":74335,"journal":{"name":"Observational studies","volume":"7 1","pages":"171 - 174"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43750897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A Melting Pot 熔炉
Observational studies Pub Date : 2021-07-27 DOI: 10.1353/obs.2021.0012
R. Tibshirani, T. Hastie
{"title":"A Melting Pot","authors":"R. Tibshirani, T. Hastie","doi":"10.1353/obs.2021.0012","DOIUrl":"https://doi.org/10.1353/obs.2021.0012","url":null,"abstract":"Abstract:Leo Breiman's article \"Statistical Modeling: The two cultures\" was timely and provocative. He advocated for Statisticians to learn about and appreciate a different \"culture\": an algorithmic approach, as distinct from the familiar, stochastic, data modeling approach to Statistics. While we have appreciated and contributed to the algorithmic approach, we have always had a foot in both camps. Here we advocate for a \"melting pot\", arguing that both approaches have their virtues, sometimes on the same problem.","PeriodicalId":74335,"journal":{"name":"Observational studies","volume":"7 1","pages":"213 - 215"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1353/obs.2021.0012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44567597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信