IF 1.7 4区数学

Stat Pub Date : 2024-05-08 DOI: 10.1002/sta4.680

Michael T. Gorczyca, Chaeryon Kang

{"title":"On quantifying heterogeneous treatment effects with regression‐based individualized treatment rules: Loss function families and bounds on estimation error","authors":"Michael T. Gorczyca, Chaeryon Kang","doi":"10.1002/sta4.680","DOIUrl":"https://doi.org/10.1002/sta4.680","url":null,"abstract":"SummaryHeterogeneity in response to treatment is a pervasive problem in medicine. Many researchers have proposed individualized treatment rule methods for this problem, which personalize treatment recommendations based on an individual's recorded covariates. A challenge with using these methods in practice is that they determine a treatment rule, rather than quantify treatment benefit. This can be problematic, as a recommended treatment could be burdensome and have negligible improvements in outcome for some individuals. With the aim of helping practitioners make informed modelling choices, we identify two families of loss functions to use with individualized treatment rule methods. Under the assumption of correct model specification, estimation with a loss function from one family ensures that the model's treatment recommendations can be interpreted in terms of the risk difference, while the other family of loss functions ensures that the model's treatment recommendations can be interpreted in terms of the risk ratio. We also derive two upper bounds for a model's error in risk difference and risk ratio estimation. Each upper bound can be calculated using observed data and can provide insight to practitioners regarding model error in estimating treatment effects. We illustrate our contributions with simulation studies as well as with data from the ACTG‐175 AIDS study.","PeriodicalId":56159,"journal":{"name":"Stat","volume":"357 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140942412","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}

引用次数: 0

Methods for building a staff workforce of quantitative scientists in academic health care 建立学术医疗定量科学家队伍的方法

IF 1.7 4区数学

Stat Pub Date : 2024-05-06 DOI: 10.1002/sta4.683

Sarah Peskoe, Emily Slade, Lacey Rende, Mary Boulos, Manisha Desai, Mihir Gandhi, Jonathan A. L. Gelfond, Shokoufeh Khalatbari, Phillip J. Schulte, Denise C. Snyder, Sandra L. Taylor, Jesse D. Troy, Roger Vaughan, Gina‐Maria Pomann

{"title":"Methods for building a staff workforce of quantitative scientists in academic health care","authors":"Sarah Peskoe, Emily Slade, Lacey Rende, Mary Boulos, Manisha Desai, Mihir Gandhi, Jonathan A. L. Gelfond, Shokoufeh Khalatbari, Phillip J. Schulte, Denise C. Snyder, Sandra L. Taylor, Jesse D. Troy, Roger Vaughan, Gina‐Maria Pomann","doi":"10.1002/sta4.683","DOIUrl":"https://doi.org/10.1002/sta4.683","url":null,"abstract":"Collaborative quantitative scientists, including biostatisticians, epidemiologists, bioinformaticists, and data‐related professionals, play vital roles in research, from study design to data analysis and dissemination. It is imperative that academic health care centers (AHCs) establish an environment that provides opportunities for the quantitative scientists who are hired as staff to develop and advance their careers. With the rapid growth of clinical and translational research, AHCs are charged with establishing organizational methods, training tools, best practices, and guidelines to accelerate and support hiring, training, and retaining this staff workforce. This paper describes three essential elements for building and maintaining a successful unit of collaborative staff quantitative scientists in academic health care centers: (1) organizational infrastructure and management, (2) recruitment, and (3) career development and retention. Specific strategies are provided as examples of how AHCs can excel in these areas.","PeriodicalId":56159,"journal":{"name":"Stat","volume":"42 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140883732","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}

引用次数: 0

Considerations in developing a financial model for an academic statistical consulting centre 为学术统计咨询中心制定财务模式的考虑因素

IF 1.7 4区数学

Stat Pub Date : 2024-05-02 DOI: 10.1002/sta4.688

Christy Brown, Yanming Di, Stacey Slone

引用次数: 0

Maximum a posteriori estimation in graphical models using local linear approximation 利用局部线性近似在图形模型中进行最大后验估计

IF 1.7 4区数学

Stat Pub Date : 2024-05-01 DOI: 10.1002/sta4.682

Ksheera Sagar, Jyotishka Datta, Sayantan Banerjee, Anindya Bhadra

引用次数: 0

Generalised minimum moment aberration for designs with both qualitative and quantitative factors 具有定性和定量因素的设计的广义最小矩差

IF 1.7 4区数学

Stat Pub Date : 2024-05-01 DOI: 10.1002/sta4.684

Yao Xiao, Na Zou, Hong Qin, Kang Wang

引用次数: 0

A sparse empirical Bayes approach to high‐dimensional Gaussian process‐based varying coefficient models 基于高斯过程的高维变化系数模型的稀疏经验贝叶斯方法

IF 1.7 4区数学

Stat Pub Date : 2024-04-20 DOI: 10.1002/sta4.678

Myungjin Kim, Gyuhyeong Goh

引用次数: 0

The value of flexible funding for collaborative biostatistics units in universities and academic medical centres 为大学和学术医学中心的合作生物统计单位提供灵活资金的价值

IF 1.7 4区数学

Stat Pub Date : 2024-04-20 DOI: 10.1002/sta4.679

Emily Slade, Sarah Jane K. Robbins, Kristen J. McQuerry, Anthony A. Mangino

{"title":"The value of flexible funding for collaborative biostatistics units in universities and academic medical centres","authors":"Emily Slade, Sarah Jane K. Robbins, Kristen J. McQuerry, Anthony A. Mangino","doi":"10.1002/sta4.679","DOIUrl":"https://doi.org/10.1002/sta4.679","url":null,"abstract":"Collaborative biostatistics units within universities and academic medical centres operate under a wide range of different funding models; common to many of these models is the challenge of allocating time to activities that are not linked to a specific research project, such as professional development, mentorship and administrative tasks. The purpose of this paper is to describe a proposed model for ‘flexible funding’, that is, funding that is not linked to a specific research project, within a collaborative biostatistics unit and to detail the benefits and challenges associated with the proposed model. We present results from a qualitative study representing the perspectives of collaborative biostatisticians working under the proposed flexible funding model. In addition to providing examples of activities undertaken as part of time allocated to flexible funding, the qualitative results reveal several benefits of flexible funding both for a collaborative biostatistician (e.g., job satisfaction and professional development) and for the collaborative biostatistics unit as a whole (e.g., retention, process improvement, and leadership).","PeriodicalId":56159,"journal":{"name":"Stat","volume":"35 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140627162","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}

引用次数: 0

Using extreme value theory to evaluate the leading pedestrian interval road safety intervention 利用极值理论评估领先的行人间隔道路安全干预措施

IF 1.7 4区数学

Stat Pub Date : 2024-04-18 DOI: 10.1002/sta4.676

Nicola Hewett, Lee Fawcett, Andrew Golightly, Neil Thorpe

{"title":"Using extreme value theory to evaluate the leading pedestrian interval road safety intervention","authors":"Nicola Hewett, Lee Fawcett, Andrew Golightly, Neil Thorpe","doi":"10.1002/sta4.676","DOIUrl":"https://doi.org/10.1002/sta4.676","url":null,"abstract":"Improving road safety is hugely important with the number of deaths on the world's roads remaining unacceptably high; an estimated 1.3 million people die each year as a result of road traffic collisions. Current practice for treating collision hotspots is almost always reactive: once a threshold level of collisions has been overtopped during some pre‐determined observation period, treatment is applied (e.g., road safety cameras). Traffic collisions are rare, so prolonged observation periods are necessary. However, traffic conflicts are more frequent and are a margin of the social cost; hence, traffic conflict before/after studies can be conducted over shorter time periods. We investigate the effect of implementing the leading pedestrian interval treatment at signalised intersections as a safety intervention in a city in north America. Pedestrian‐vehicle traffic conflict data were collected from treatment and control sites during the before and after periods. We implement a before/after study on post‐encroachment times (PETs) where small PET values denote ‘near‐misses’. Hence, extreme value theory is employed to model extremes of our PET processes, with adjustments to the usual modelling framework to account for temporal dependence and treatment effects.","PeriodicalId":56159,"journal":{"name":"Stat","volume":"10 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140626894","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}

引用次数: 0

The data science discovery program: A model for data science consulting in higher education 数据科学发现计划：高等教育数据科学咨询模式

IF 1.7 4区数学

Stat Pub Date : 2024-04-18 DOI: 10.1002/sta4.677

C. Taylor Brown, Megan Mehta, Mahathi Ryali, Xiaoran Dong, Iliya Shadfar, Jacqueline Dominquez Davalos, Aaron Culich, Anthony Suen

{"title":"The data science discovery program: A model for data science consulting in higher education","authors":"C. Taylor Brown, Megan Mehta, Mahathi Ryali, Xiaoran Dong, Iliya Shadfar, Jacqueline Dominquez Davalos, Aaron Culich, Anthony Suen","doi":"10.1002/sta4.677","DOIUrl":"https://doi.org/10.1002/sta4.677","url":null,"abstract":"As one of the largest data science research incubator initiatives in the country, the University of California, Berkeley's Data Science Discovery Program serves as a case study for a scalable and sustainable model of data science consulting in higher education. This case contributes to the broader literature on data science consulting in higher education by analysing the programme's development, institutional influences; staffing and structural model; and defining features, which may prove instructive to similar programmes at other institutions. The programme is characterised by a unique structure of undergraduate consultations led by graduate student mentorship and governance; a streamlined, multidepartmental model that facilitates scalability and sustainability; and diverse modes for undergraduate consulting—including one‐on‐one ad‐hoc data science consultations, extended data science project development and management, peer mentorship and data science workshop instruction. This case demonstrates that universities may be able to initiate a low‐stakes, small‐scale data science consulting initiative and then progressively scale up the project in collaboration with multiple departments and organisations across campus.","PeriodicalId":56159,"journal":{"name":"Stat","volume":"78 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140630597","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}

引用次数: 0

Utilizing latent connectivity among mediators in high-dimensional mediation analysis 在高维中介分析中利用中介人之间的潜在关联性

IF 1.7 4区数学

Stat Pub Date : 2024-04-16 DOI: 10.1002/sta4.675

Jia Yuan Hu, Marley DeSimone, Qing Wang

{"title":"Utilizing latent connectivity among mediators in high-dimensional mediation analysis","authors":"Jia Yuan Hu, Marley DeSimone, Qing Wang","doi":"10.1002/sta4.675","DOIUrl":"https://doi.org/10.1002/sta4.675","url":null,"abstract":"Mediation analysis intends to unveil the underlying relationship between an outcome variable and an exposure variable through one or more intermediate variables called mediators. In recent decades, research on mediation analysis has been focusing on multivariate mediation models, where the number of mediating variables is possibly of high dimension. This paper concerns high-dimensional mediation analysis and proposes a three-step algorithm that extracts and utilizes inter-connectivity among candidate mediators. More specifically, the proposed methodology starts with a screening procedure to reduce the dimensionality of the initial set of candidate mediators, followed by a penalized regression model that incorporates both parameter- and group-wise regularization, and ends with fitting a multivariate mediation model and identifying active mediating variables through a joint significance test. To showcase the performance of the proposed algorithm, we conducted two simulation studies in high-dimensional and ultra-high-dimensional settings, respectively. Furthermore, we demonstrate the practical applications of the proposal using a real data set that uncovers the possible impact of environmental toxicants on women's gestational age at delivery through 61 biomarkers that belong to 7 biological pathways.","PeriodicalId":56159,"journal":{"name":"Stat","volume":"57 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140583973","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}

引用次数: 0

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