Journal of the Royal Statistical Society Series A-Statistics in Society最新文献

A framework for understanding selection bias in real-world healthcare data. 了解真实世界医疗数据中选择偏差的框架。

IF 1.5 3区数学

Journal of the Royal Statistical Society Series A-Statistics in Society Pub Date : 2024-05-02 eCollection Date: 2024-08-01 DOI: 10.1093/jrsssa/qnae039

Ritoban Kundu, Xu Shi, Jean Morrison, Jessica Barrett, Bhramar Mukherjee

{"title":"A framework for understanding selection bias in real-world healthcare data.","authors":"Ritoban Kundu, Xu Shi, Jean Morrison, Jessica Barrett, Bhramar Mukherjee","doi":"10.1093/jrsssa/qnae039","DOIUrl":"10.1093/jrsssa/qnae039","url":null,"abstract":"<p><p>Using administrative patient-care data such as Electronic Health Records (EHR) and medical/pharmaceutical claims for population-based scientific research has become increasingly common. With vast sample sizes leading to very small standard errors, researchers need to pay more attention to potential biases in the estimates of association parameters of interest, specifically to biases that do not diminish with increasing sample size. Of these multiple sources of biases, in this paper, we focus on understanding selection bias. We present an analytic framework using directed acyclic graphs for guiding applied researchers to dissect how different sources of selection bias may affect estimates of the association between a binary outcome and an exposure (continuous or categorical) of interest. We consider four easy-to-implement weighting approaches to reduce selection bias with accompanying variance formulae. We demonstrate through a simulation study when they can rescue us in practice with analysis of real-world data. We compare these methods using a data example where our goal is to estimate the well-known association of cancer and biological sex, using EHR from a longitudinal biorepository at the University of Michigan Healthcare system. We provide annotated R codes to implement these weighted methods with associated inference.</p>","PeriodicalId":49983,"journal":{"name":"Journal of the Royal Statistical Society Series A-Statistics in Society","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11393555/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142299713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Measuring Social Inclusion in Europe: a non-additive approach with the expert-preferences of public policy planners. 衡量欧洲的社会包容情况：利用公共政策规划者的专家偏好的非加法方法。

IF 2 3区数学

Journal of the Royal Statistical Society Series A-Statistics in Society Pub Date : 2023-09-05 eCollection Date: 2024-01-01 DOI: 10.1093/jrsssa/qnad106

Ludovico Carrino, Luca Farnia, Silvio Giove

引用次数: 0

Dr Arun Chind’s contribution to the Discussion of “A system of population estimates compiled from administrative data only” by Dunne and Zhang Dr . Arun china对Dunne和Zhang关于“仅从行政数据编制的人口估计系统”的讨论的贡献

IF 2 3区数学

Journal of the Royal Statistical Society Series A-Statistics in Society Pub Date : 2023-08-31 DOI: 10.1093/jrsssa/qnad119

A. Chind

引用次数: 0

The Psychometrics of Standard Setting 标准制定的心理测量学

IF 2 3区数学

Journal of the Royal Statistical Society Series A-Statistics in Society Pub Date : 2023-08-22 DOI: 10.1093/jrsssa/qnad108

Andrew Mcculloch

引用次数: 0

Measurement Models for Psychological Attributes 心理属性的测量模型

IF 2 3区数学

Journal of the Royal Statistical Society Series A-Statistics in Society Pub Date : 2023-08-22 DOI: 10.1093/jrsssa/qnad107

Andrew Mcculloch

引用次数: 0

Data Science Ethics: Concepts, Techniques and Cautionary Tales 数据科学伦理:概念、技术和警示故事

IF 2 3区数学

Journal of the Royal Statistical Society Series A-Statistics in Society Pub Date : 2023-08-14 DOI: 10.1093/jrsssa/qnad111

R. Reese

引用次数: 0

Big Data and Social Science Data Science Methods and Tools for Research and Practice 大数据与社会科学研究与实践的数据科学方法与工具

IF 2 3区数学

Journal of the Royal Statistical Society Series A-Statistics in Society Pub Date : 2023-08-14 DOI: 10.1093/jrsssa/qnad109

V. Kalyani

引用次数: 0

Sarah Henry and Katie O’Farrell’s contribution to the Discussion of 'A system of population estimates compiled from administrative data only' by John Dunne and Li-Chun Zhang Sarah Henry和Katie O ' farrell对John Dunne和Li-Chun Zhang关于“仅从行政数据编制的人口估计系统”的讨论的贡献

IF 2 3区数学

Journal of the Royal Statistical Society Series A-Statistics in Society Pub Date : 2023-08-11 DOI: 10.1093/jrsssa/qnad095

Sarah Henry, K. O’Farrell

引用次数: 0

Biostatistics Decoded 生物统计学解码

IF 2 3区数学

Journal of the Royal Statistical Society Series A-Statistics in Society Pub Date : 2023-08-08 DOI: 10.1093/jrsssa/qnad093

Mukesh Srivastava

{"title":"Biostatistics Decoded","authors":"Mukesh Srivastava","doi":"10.1093/jrsssa/qnad093","DOIUrl":"https://doi.org/10.1093/jrsssa/qnad093","url":null,"abstract":"Description: Study design and statistical methodology are two important concerns for the clinical researcher. This book sets out to address both issues in a clear and concise manner. The presentation of statistical theory starts from basic concepts, such as the properties of means and variances, the properties of the Normal distribution and the Central Limit Theorem and leads to more advanced topics such as maximum likelihood estimation, inverse variance and stepwise regression as well as, time–to–event, and event–count methods. Furthermore, this book explores sampling methods, study design and statistical methods and is organized according to the areas of application of each of the statistical methods and the corresponding study designs. Illustrations, working examples, computer simulations and geometrical approaches, rather than mathematical expressions and formulae, are used throughout the book to explain every statistical method. Biostatisticians and researchers in the medical and pharmaceutical industry who need guidance on the design and analyis of medical research will find this book useful as well as graduate students of statistics and mathematics with an interest in biostatistics Biostatistics Decoded:-Provides clear explanations of key statistical concepts with a firm emphasis on practical aspects of design and analysis of medical research.-Features worked examples to illustrate each statistical method using computer simulations and geometrical approaches, rather than mathematical expressions and formulae.-Explores the main types of clinical research studies, such as, descriptive, analytical and experimental studies.-Addresses advanced modeling techniques such as interaction analysis and encoding by reference and polynomial regression.","PeriodicalId":49983,"journal":{"name":"Journal of the Royal Statistical Society Series A-Statistics in Society","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2023-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74724939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Heterogeneity in the US gender wage gap 美国性别工资差距的异质性

IF 2 3区数学

Journal of the Royal Statistical Society Series A-Statistics in Society Pub Date : 2023-08-08 DOI: 10.1093/jrsssa/qnad091

Philipp Bach, V. Chernozhukov, M. Spindler

引用次数: 0