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

Assessments and developments in constructing a National Health Index for policy-making, in the UK 英国在构建用于决策的国民健康指数方面的评估和发展情况

Journal of the Royal Statistical Society Series A: Statistics in Society Pub Date : 2024-07-26 DOI: 10.1093/jrsssa/qnae060

A. Freni-Sterrantino, Thomas P Prescott, Greg Ceely, Myer Glickman, Chris Holmes

引用次数: 0

Introduction to Environmental Data Science 环境数据科学入门

Journal of the Royal Statistical Society Series A: Statistics in Society Pub Date : 2024-07-25 DOI: 10.1093/jrsssa/qnae071

Nicholas J. Cox

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Introduction to the special issue based on contributions from ‘A celebration of 50 Years of the Cox model in memory of Sir David Cox’, 10 November 2022, London School of Hygiene & Tropical Medicine 根据 "纪念大卫-考克斯爵士考克斯模型 50 周年庆典"（2022 年 11 月 10 日，伦敦卫生与热带医学学院）的来稿编写的特刊导言

Journal of the Royal Statistical Society Series A: Statistics in Society Pub Date : 2024-07-17 DOI: 10.1093/jrsssa/qnae062

Ruth H. Keogh

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Eamonn (Edward) McEntee, 1934–2024 埃蒙（爱德华）-麦肯提（Eamonn (Edward) McEntee），1934-2024 年

Journal of the Royal Statistical Society Series A: Statistics in Society Pub Date : 2024-07-16 DOI: 10.1093/jrsssa/qnae055

G. Mackenzie, Edward Goodall

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A censored quantile transformation model for Alzheimer’s Disease data with multiple functional covariates 具有多种功能协变量的阿尔茨海默病数据的删减量子转换模型

Journal of the Royal Statistical Society Series A: Statistics in Society Pub Date : 2024-07-11 DOI: 10.1093/jrsssa/qnae061

Shaopei Ma, Man-lai Tang, Keming Yu, W. Härdle, Zhihao Wang, Wei Xiong, Xueliang Zhang, Kai Wang, Liping Zhang, Maozai Tian

{"title":"A censored quantile transformation model for Alzheimer’s Disease data with multiple functional covariates","authors":"Shaopei Ma, Man-lai Tang, Keming Yu, W. Härdle, Zhihao Wang, Wei Xiong, Xueliang Zhang, Kai Wang, Liping Zhang, Maozai Tian","doi":"10.1093/jrsssa/qnae061","DOIUrl":"https://doi.org/10.1093/jrsssa/qnae061","url":null,"abstract":"\u0000 Alzheimer’s disease (AD) is a progressive disease that starts from mild cognitive impairment and may eventually lead to irreversible memory loss. It is imperative to explore the risk factors associated with the conversion time to AD that is usually right-censored. Classical statistical models like mean regression and Cox models fail to quantify the impact of risk factors across different quantiles of a response distribution, and previous research has primarily focused on modelling a single functional covariate, possibly overlooking the interdependence among multiple functional covariates and other crucial features of the distribution. To address these issues, this paper proposes a multivariate functional censored quantile regression model based on dynamic power transformations, which relaxes the global linear assumption and provides more robustness and flexibility. Uniform consistency and weak convergence of the quantile process are established. Simulation studies suggest that the proposed method outperforms the existing approaches. Real data analysis shows the importance of both left and right hippocampal radial distance curves for predicting the conversion time to AD at different quantile levels.","PeriodicalId":506281,"journal":{"name":"Journal of the Royal Statistical Society Series A: Statistics in Society","volume":"10 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141655927","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

Data Science: A First Introduction 数据科学：数据科学入门

Journal of the Royal Statistical Society Series A: Statistics in Society Pub Date : 2024-06-15 DOI: 10.1093/jrsssa/qnae057

Shalabh

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Foundations of Statistics for Data Scientists with R and Python 使用 R 和 Python 的数据科学家统计基础

Journal of the Royal Statistical Society Series A: Statistics in Society Pub Date : 2024-06-10 DOI: 10.1093/jrsssa/qnae054

Sandipan Roy

引用次数: 0

Principles of Statistical Analyses: Learning from Randomized Experiments 统计分析原理：从随机实验中学习

Journal of the Royal Statistical Society Series A: Statistics in Society Pub Date : 2024-05-24 DOI: 10.1093/jrsssa/qnae052

Egor Bronnikov

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Re-weighting the randomized controlled trial for generalization: finite-sample error and variable selection 重新加权随机对照试验以推广：有限样本误差和变量选择

Journal of the Royal Statistical Society Series A: Statistics in Society Pub Date : 2024-05-24 DOI: 10.1093/jrsssa/qnae043

B. Colnet, Julie Josse, G. Varoquaux, Erwan Scornet

{"title":"Re-weighting the randomized controlled trial for generalization: finite-sample error and variable selection","authors":"B. Colnet, Julie Josse, G. Varoquaux, Erwan Scornet","doi":"10.1093/jrsssa/qnae043","DOIUrl":"https://doi.org/10.1093/jrsssa/qnae043","url":null,"abstract":"\u0000 Randomized controlled trials (RCTs) may suffer from limited scope. In particular, samples may be unrepresentative: some RCTs over- or under-sample individuals with certain characteristics compared to the target population, for which one wants conclusions on treatment effectiveness. Re-weighting trial individuals to match the target population can improve the treatment effect estimation. In this work, we establish the expressions of the bias and variance of such re-weighting procedures—also called inverse propensity of sampling weighting (IPSW)—in presence of categorical covariates for any sample size. Such results allow us to compare the theoretical performance of different versions of IPSW estimates. Besides, our results show how the performance (bias, variance, and quadratic risk) of IPSW estimates depends on the two sample sizes (RCT and target population). A by-product of our work is the proof of consistency of IPSW estimates. In addition, we analyse how including covariates that are not necessary for identifiability of the causal effect may impact the asymptotic variance. Including covariates that are shifted between the two samples but not treatment-effect modifiers increases the variance while non-shifted but treatment-effect modifiers do not. We illustrate all the takeaways in a didactic example, and on a semi-synthetic simulation inspired from critical care medicine.","PeriodicalId":506281,"journal":{"name":"Journal of the Royal Statistical Society Series A: Statistics in Society","volume":"90 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141100970","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

Some recollections of the early years of the Medical Research Council Statistical Research Unit 医学研究理事会统计研究组早年的一些回忆

Journal of the Royal Statistical Society Series A: Statistics in Society Pub Date : 2024-05-17 DOI: 10.1093/jrsssa/qnae024

Peter Armitage

引用次数: 0