arXiv - STAT - Other Statistics最新文献_第4页

Guidelines and Best Practices to Share Deidentified Data and Code 共享去标识化数据和代码的指导原则和最佳做法

arXiv - STAT - Other Statistics Pub Date : 2024-05-28 DOI: arxiv-2405.18232

Nicholas J. Horton, Sara Stoudt

{"title":"Guidelines and Best Practices to Share Deidentified Data and Code","authors":"Nicholas J. Horton, Sara Stoudt","doi":"arxiv-2405.18232","DOIUrl":"https://doi.org/arxiv-2405.18232","url":null,"abstract":"In 2022, the Journal of Statistics and Data Science Education (JSDSE)\u0000instituted augmented requirements for authors to post deidentified data and\u0000code underlying their papers. These changes were prompted by an increased focus\u0000on reproducibility and open science (NASEM 2019). A recent review of data\u0000availability practices noted that \"such policies help increase the\u0000reproducibility of the published literature, as well as make a larger body of\u0000data available for reuse and re-analysis\" (PLOS ONE, 2024). JSDSE values\u0000accessibility as it endeavors to share knowledge that can improve educational\u0000approaches to teaching statistics and data science. Because institution,\u0000environment, and students differ across readers of the journal, it is\u0000especially important to facilitate the transfer of a journal article's findings\u0000to new contexts. This process may require digging into more of the details,\u0000including the deidentified data and code. Our goal is to provide our readers\u0000and authors with a review of why the requirements for code and data sharing\u0000were instituted, summarize ongoing trends and developments in open science,\u0000discuss options for data and code sharing, and share advice for authors.","PeriodicalId":501323,"journal":{"name":"arXiv - STAT - Other Statistics","volume":"133 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141171713","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

The Epistemology behind Covariate Adjustment 变量调整背后的认识论

arXiv - STAT - Other Statistics Pub Date : 2024-05-27 DOI: arxiv-2405.17224

Grayson L. Baird, Stephen L. Bieber

引用次数: 0

The Logic of Counterfactuals and the Epistemology of Causal Inference 反事实逻辑与因果推理认识论

arXiv - STAT - Other Statistics Pub Date : 2024-05-18 DOI: arxiv-2405.11284

Hanti Lin

引用次数: 0

Expected Points Above Average: A Novel NBA Player Metric Based on Bayesian Hierarchical Modeling 平均预期得分：基于贝叶斯层次模型的新型 NBA 球员衡量标准

arXiv - STAT - Other Statistics Pub Date : 2024-05-16 DOI: arxiv-2405.10453

Benjamin Williams, Erin M. Schliep, Bailey Fosdick, Ryan Elmore

引用次数: 0

Identification of Single-Treatment Effects in Factorial Experiments 因子实验中单一处理效应的识别

arXiv - STAT - Other Statistics Pub Date : 2024-05-16 DOI: arxiv-2405.09797

Guilherme Duarte

{"title":"Identification of Single-Treatment Effects in Factorial Experiments","authors":"Guilherme Duarte","doi":"arxiv-2405.09797","DOIUrl":"https://doi.org/arxiv-2405.09797","url":null,"abstract":"Despite their cost, randomized controlled trials (RCTs) are widely regarded\u0000as gold-standard evidence in disciplines ranging from social science to\u0000medicine. In recent decades, researchers have increasingly sought to reduce the\u0000resource burden of repeated RCTs with factorial designs that simultaneously\u0000test multiple hypotheses, e.g. experiments that evaluate the effects of many\u0000medications or products simultaneously. Here I show that when multiple\u0000interventions are randomized in experiments, the effect any single intervention\u0000would have outside the experimental setting is not identified absent heroic\u0000assumptions, even if otherwise perfectly realistic conditions are achieved.\u0000This happens because single-treatment effects involve a counterfactual world\u0000with a single focal intervention, allowing other variables to take their\u0000natural values (which may be confounded or modified by the focal intervention).\u0000In contrast, observational studies and factorial experiments provide\u0000information about potential-outcome distributions with zero and multiple\u0000interventions, respectively. In this paper, I formalize sufficient conditions\u0000for the identifiability of those isolated quantities. I show that researchers\u0000who rely on this type of design have to justify either linearity of functional\u0000forms or -- in the nonparametric case -- specify with Directed Acyclic Graphs\u0000how variables are related in the real world. Finally, I develop nonparametric\u0000sharp bounds -- i.e., maximally informative best-/worst-case estimates\u0000consistent with limited RCT data -- that show when extrapolations about effect\u0000signs are empirically justified. These new results are illustrated with\u0000simulated data.","PeriodicalId":501323,"journal":{"name":"arXiv - STAT - Other Statistics","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141062584","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

Sequential Maximal Updated Density Parameter Estimation for Dynamical Systems with Parameter Drift 有参数漂移的动态系统的序列最大更新密度参数估计

arXiv - STAT - Other Statistics Pub Date : 2024-05-14 DOI: arxiv-2405.08307

Carlos del-Castillo-Negrete, Rylan Spence, Troy Butler, Clint Dawson

{"title":"Sequential Maximal Updated Density Parameter Estimation for Dynamical Systems with Parameter Drift","authors":"Carlos del-Castillo-Negrete, Rylan Spence, Troy Butler, Clint Dawson","doi":"arxiv-2405.08307","DOIUrl":"https://doi.org/arxiv-2405.08307","url":null,"abstract":"We present a novel method for generating sequential parameter estimates and\u0000quantifying epistemic uncertainty in dynamical systems within a data-consistent\u0000(DC) framework. The DC framework differs from traditional Bayesian approaches\u0000due to the incorporation of the push-forward of an initial density, which\u0000performs selective regularization in parameter directions not informed by the\u0000data in the resulting updated density. This extends a previous study that\u0000included the linear Gaussian theory within the DC framework and introduced the\u0000maximal updated density (MUD) estimate as an alternative to both least squares\u0000and maximum a posterior (MAP) estimates. In this work, we introduce algorithms\u0000for operational settings of MUD estimation in real or near-real time where\u0000spatio-temporal datasets arrive in packets to provide updated estimates of\u0000parameters and identify potential parameter drift. Computational diagnostics\u0000within the DC framework prove critical for evaluating (1) the quality of the DC\u0000update and MUD estimate and (2) the detection of parameter value drift. The\u0000algorithms are applied to estimate (1) wind drag parameters in a high-fidelity\u0000storm surge model, (2) thermal diffusivity field for a heat conductivity\u0000problem, and (3) changing infection and incubation rates of an epidemiological\u0000model.","PeriodicalId":501323,"journal":{"name":"arXiv - STAT - Other Statistics","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140941397","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

Predicting Short Response Ratings with Non-Content Related Features: A Hierarchical Modeling Approach 利用与内容无关的特征预测简短回复评分：分层建模方法

arXiv - STAT - Other Statistics Pub Date : 2024-05-14 DOI: arxiv-2405.08574

Aubrey Condor

引用次数: 0

Nested Instrumental Variables Design: Switcher Average Treatment Effect, Identification, Efficient Estimation and Generalizability 嵌套工具变量设计：转换者平均治疗效果、识别、有效估计和普适性

arXiv - STAT - Other Statistics Pub Date : 2024-05-11 DOI: arxiv-2405.07102

Rui Wang, Ying-Qi Zhao, Oliver Dukes, Bo Zhang

{"title":"Nested Instrumental Variables Design: Switcher Average Treatment Effect, Identification, Efficient Estimation and Generalizability","authors":"Rui Wang, Ying-Qi Zhao, Oliver Dukes, Bo Zhang","doi":"arxiv-2405.07102","DOIUrl":"https://doi.org/arxiv-2405.07102","url":null,"abstract":"Instrumental variables (IV) are a commonly used tool to estimate causal\u0000effects from non-randomized data. A prototype of an IV is a randomized trial\u0000with non-compliance where the randomized treatment assignment serves as an IV\u0000for the non-ignorable treatment received. Under a monotonicity assumption, a\u0000valid IV non-parametrically identifies the average treatment effect among a\u0000non-identifiable complier subgroup, whose generalizability is often under\u0000debate. In many studies, there could exist multiple versions of an IV, for\u0000instance, different nudges to take the same treatment in different study sites\u0000in a multi-center clinical trial. These different versions of an IV may result\u0000in different compliance rates and offer a unique opportunity to study IV\u0000estimates' generalizability. In this article, we introduce a novel nested IV\u0000assumption and study identification of the average treatment effect among two\u0000latent subgroups: always-compliers and switchers, who are defined based on the\u0000joint potential treatment received under two versions of a binary IV. We derive\u0000the efficient influence function for the SWitcher Average Treatment Effect\u0000(SWATE) and propose efficient estimators. We then propose formal statistical\u0000tests of the generalizability of IV estimates based on comparing the\u0000conditional average treatment effect among the always-compliers and that among\u0000the switchers under the nested IV framework. We apply the proposed framework\u0000and method to the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer\u0000Screening Trial and study the causal effect of colorectal cancer screening and\u0000its generalizability.","PeriodicalId":501323,"journal":{"name":"arXiv - STAT - Other Statistics","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140941495","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

Strategies for Rare Population Detection and Sampling: A Methodological Approach in Liguria 稀有种群检测和采样策略：利古里亚的方法论途径

arXiv - STAT - Other Statistics Pub Date : 2024-05-02 DOI: arxiv-2405.01342

G. Lancia, E. Riccomagno

{"title":"Strategies for Rare Population Detection and Sampling: A Methodological Approach in Liguria","authors":"G. Lancia, E. Riccomagno","doi":"arxiv-2405.01342","DOIUrl":"https://doi.org/arxiv-2405.01342","url":null,"abstract":"Economic policy sciences are constantly investigating the quality of\u0000well-being of broad sections of the population in order to describe the current\u0000interdependence between unequal living conditions, low levels of education and\u0000a lack of integration into society. Such studies are often carried out in the\u0000form of surveys, e.g. as part of the EU-SILC program. If the survey is designed\u0000at national or international level, the results of the study are often used as\u0000a reference by a broad range of public institutions. However, the sampling\u0000strategy per se may not capture enough information to provide an accurate\u0000representation of all population strata. Problems might arise from rare, or\u0000hard-to-sample, populations and the conclusion of the study may be compromised\u0000or unrealistic. We propose here a two-phase methodology to identify rare,\u0000poorly sampled populations and then resample the hard-to-sample strata. We\u0000focused our attention on the 2019 EU-SILC section concerning the Italian region\u0000of Liguria. Methods based on dispersion indices or deep learning were used to\u0000detect rare populations. A multi-frame survey was proposed as the sampling\u0000design. The results showed that factors such as citizenship, material\u0000deprivation and large families are still fundamental characteristics that are\u0000difficult to capture.","PeriodicalId":501323,"journal":{"name":"arXiv - STAT - Other Statistics","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140828627","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

What's So Hard about the Monty Hall Problem? 蒙蒂-霍尔问题有什么难的？

arXiv - STAT - Other Statistics Pub Date : 2024-05-01 DOI: arxiv-2405.00884

Rafael C. Alvarado

引用次数: 0