• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

纵向轨迹建模中损耗加权调整的作用：一项模拟研究

The Role of Weighting Adjustment for Attrition in Longitudinal Trajectory Modeling: A Simulation Study.

作者信息

West Brady T, Si Yajuan, Hu Yueying, McCabe Sean E, Veliz Phil

机构信息

Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor; Department of Biostatistics, University of Michigan, Ann Arbor; Center for the Study of Drugs, Alcohol, Smoking and Health, Department of Health Behavior and Biological Sciences, School of Nursing, University of Michigan, Ann Arbor.

Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor; Department of Biostatistics, University of Michigan, Ann Arbor.

出版信息

Commun Stat Simul Comput. 2025;54(3):866-888. doi: 10.1080/03610918.2024.2362923. Epub 2024 Jun 7.

DOI:10.1080/03610918.2024.2362923
PMID:40270979
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12014153/
Abstract

Most longitudinal surveys construct weights and release wave-specific weights to adjust for attrition. However, there is no clear consensus in the literature on whether or how to apply weights in longitudinal trajectory modeling. We present a simulation study, motivated by a real-life longitudinal study of substance use, and consider different missing data mechanisms, weight construction processes, and specifications of substantive models of interest. Based on the results of the simulation study, we provide practical recommendations for analysts of longitudinal survey data with respect to weighting approaches that should be considered in alternative scenarios.

摘要

大多数纵向调查都会构建权重并发布特定波次的权重，以调整样本流失问题。然而，对于在纵向轨迹建模中是否应用权重以及如何应用权重，文献中尚无明确的共识。我们开展了一项模拟研究，该研究受一项关于物质使用的实际纵向研究启发，并考虑了不同的缺失数据机制、权重构建过程以及感兴趣的实质性模型的设定。基于模拟研究的结果，我们针对纵向调查数据的分析人员，就不同场景下应考虑的加权方法提供了实用建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/c085026863f7/nihms-2003281-f0009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/2fd5aaa3e61d/nihms-2003281-f0010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/0c99bec2255a/nihms-2003281-f0011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/1cfb91152784/nihms-2003281-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/d9fe51502871/nihms-2003281-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/53eb5ef4b5e4/nihms-2003281-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/29a73370d651/nihms-2003281-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/8d626dc3e0dc/nihms-2003281-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/16065cd49a70/nihms-2003281-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/e6b6fc7a8501/nihms-2003281-f0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/ba1bc95b96de/nihms-2003281-f0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/c085026863f7/nihms-2003281-f0009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/2fd5aaa3e61d/nihms-2003281-f0010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/0c99bec2255a/nihms-2003281-f0011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/1cfb91152784/nihms-2003281-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/d9fe51502871/nihms-2003281-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/53eb5ef4b5e4/nihms-2003281-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/29a73370d651/nihms-2003281-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/8d626dc3e0dc/nihms-2003281-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/16065cd49a70/nihms-2003281-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/e6b6fc7a8501/nihms-2003281-f0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/ba1bc95b96de/nihms-2003281-f0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bf0/12014153/c085026863f7/nihms-2003281-f0009.jpg

相似文献

1
The Role of Weighting Adjustment for Attrition in Longitudinal Trajectory Modeling: A Simulation Study.纵向轨迹建模中损耗加权调整的作用：一项模拟研究
Commun Stat Simul Comput. 2025;54(3):866-888. doi: 10.1080/03610918.2024.2362923. Epub 2024 Jun 7.
2
An empirical evaluation of alternative approaches to adjusting for attrition when analyzing longitudinal survey data on young adults' substance use trajectories.当分析关于年轻人物质使用轨迹的纵向调查数据时，对调整因流失而产生的偏差的替代方法进行实证评估。
Int J Methods Psychiatr Res. 2022 Sep;31(3):e1916. doi: 10.1002/mpr.1916. Epub 2022 May 18.
3
Incorporating the sampling design in weighting adjustments for panel attrition.将抽样设计纳入面板损耗的加权调整中。
Stat Med. 2015 Dec 10;34(28):3637-47. doi: 10.1002/sim.6618. Epub 2015 Aug 2.
4
Alternative Approaches to Assessing Nonresponse Bias in Longitudinal Survey Estimates: An Application to Substance-Use Outcomes Among Young Adults in the United States.评估纵向调查估计中非应答偏差的替代方法：在美国年轻成年人物质使用结果中的应用
Am J Epidemiol. 2017 Apr 1;185(7):591-600. doi: 10.1093/aje/kww115.
5
Attrition Bias Related to Missing Outcome Data: A Longitudinal Simulation Study.随访缺失导致的损耗偏倚：一项纵向模拟研究。
Epidemiology. 2018 Jan;29(1):87-95. doi: 10.1097/EDE.0000000000000755.
6
Methods to account for attrition in longitudinal data: do they work? A simulation study.纵向数据中处理数据缺失的方法：它们有效吗？一项模拟研究。
Eur J Epidemiol. 2005;20(8):657-62. doi: 10.1007/s10654-005-7919-7.
7
Assessment of Multiple Membership Multilevel Models: An Application to Interviewer Effects on Nonresponse.多成员多层次模型评估：对访员对无回答影响的应用。
Multivariate Behav Res. 2018 Sep-Oct;53(5):595-611. doi: 10.1080/00273171.2018.1465809. Epub 2018 May 17.
8
Analytical results in longitudinal studies depended on target of inference and assumed mechanism of attrition.纵向研究的分析结果取决于推断的目标和假设的损耗机制。
J Clin Epidemiol. 2015 Oct;68(10):1165-75. doi: 10.1016/j.jclinepi.2015.03.011. Epub 2015 Mar 31.
9
Balancing vs modeling approaches to weighting in practice.实践中加权的平衡法与建模法
Stat Med. 2020 Oct 30;39(24):3227-3254. doi: 10.1002/sim.8659. Epub 2020 Sep 3.
10
A wide range of missing imputation approaches in longitudinal data: a simulation study and real data analysis.多种缺失值插补方法在纵向数据分析中的应用：一项模拟研究与真实数据分析。
BMC Med Res Methodol. 2023 Jul 6;23(1):161. doi: 10.1186/s12874-023-01968-8.

引用本文的文献

1
Trends and Sociodemographic Differences in Tobacco/Nicotine Transitions Among U.S. Adolescents and Young Adults Using e-cigarettes, 2014-2023.2014 - 2023年美国使用电子烟的青少年和年轻人烟草/尼古丁转换的趋势及社会人口学差异
J Adolesc Health. 2025 May;76(5):920-927. doi: 10.1016/j.jadohealth.2025.01.013. Epub 2025 Feb 19.

本文引用的文献

1
An empirical evaluation of alternative approaches to adjusting for attrition when analyzing longitudinal survey data on young adults' substance use trajectories.当分析关于年轻人物质使用轨迹的纵向调查数据时，对调整因流失而产生的偏差的替代方法进行实证评估。
Int J Methods Psychiatr Res. 2022 Sep;31(3):e1916. doi: 10.1002/mpr.1916. Epub 2022 May 18.
2
ASSESSING SELECTION BIAS IN REGRESSION COEFFICIENTS ESTIMATED FROM NONPROBABILITY SAMPLES WITH APPLICATIONS TO GENETICS AND DEMOGRAPHIC SURVEYS.评估从非概率样本估计的回归系数中的选择偏差及其在遗传学和人口调查中的应用。
Ann Appl Stat. 2021 Sep;15(3):1556-1581. doi: 10.1214/21-aoas1453. Epub 2021 Sep 23.
3
Predicting risk for Alcohol Use Disorder using longitudinal data with multimodal biomarkers and family history: a machine learning study.
利用具有多模态生物标志物和家族史的纵向数据预测酒精使用障碍风险：一项机器学习研究。
Mol Psychiatry. 2021 Apr;26(4):1133-1141. doi: 10.1038/s41380-019-0534-x. Epub 2019 Oct 8.
4
Longitudinal drop-out and weighting against its bias.纵向脱落与对其偏差的加权。
BMC Med Res Methodol. 2017 Dec 8;17(1):164. doi: 10.1186/s12874-017-0446-x.
5
Selective nonresponse bias in population-based survey estimates of drug use behaviors in the United States.美国基于人群的药物使用行为调查估计中的选择性无应答偏差。
Soc Psychiatry Psychiatr Epidemiol. 2016 Jan;51(1):141-53. doi: 10.1007/s00127-015-1122-2. Epub 2015 Sep 16.
6
Missing data methods in longitudinal studies: a review.纵向研究中的缺失数据方法：综述
Test (Madr). 2009 May 1;18(1):1-43. doi: 10.1007/s11749-009-0138-x.
7
Heavy drinking across the transition to college: predicting first-semester heavy drinking from precollege variables.大学过渡期间的酗酒问题：根据大学前的变量预测第一学期的酗酒情况。
Addict Behav. 2007 Apr;32(4):819-35. doi: 10.1016/j.addbeh.2006.06.024. Epub 2006 Jul 24.
8
The problem of college drinking: insights from a developmental perspective.大学生饮酒问题：从发展角度的见解
Alcohol Clin Exp Res. 2001 Mar;25(3):473-7.