• 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

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。

An empirical evaluation of alternative approaches to adjusting for attrition when analyzing longitudinal survey data on young adults' substance use trajectories.

机构信息

Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, USA.

Department of Systems, Populations and Leadership, School of Nursing, University of Michigan, Ann Arbor, Michigan, USA.

出版信息

Int J Methods Psychiatr Res. 2022 Sep;31(3):e1916. doi: 10.1002/mpr.1916. Epub 2022 May 18.

DOI:10.1002/mpr.1916
PMID:35582963
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9464329/
Abstract

OBJECTIVES

Longitudinal survey data allow for the estimation of developmental trajectories of substance use from adolescence to young adulthood, but these estimates may be subject to attrition bias. Moreover, there is a lack of consensus regarding the most effective statistical methodology to adjust for sample selection and attrition bias when estimating these trajectories. Our objective is to develop specific recommendations regarding adjustment approaches for attrition in longitudinal surveys in practice.

METHODS

Analyzing data from the national U.S. Monitoring the Future panel study following four cohorts of individuals from modal ages 18 to 29/30, we systematically compare alternative approaches to analyzing longitudinal data with a wide range of substance use outcomes, and examine the sensitivity of inferences regarding substance use prevalence and trajectories as a function of college attendance to the approach used.

RESULTS

Our results show that analyzing all available observations in each wave, while simultaneously accounting for the correlations among repeated observations, sample selection, and attrition, is the most effective approach. The adjustment effects are pronounced in wave-specific descriptive estimates but generally modest in covariate-adjusted trajectory modeling.

CONCLUSIONS

The adjustments can refine the precision, and, to some extent, the implications of our findings regarding young adult substance use trajectories.

摘要

目的

纵向调查数据允许从青春期到青年期估计物质使用的发展轨迹,但这些估计可能受到流失偏差的影响。此外,在估计这些轨迹时,对于调整样本选择和流失偏差的最有效统计方法,尚未达成共识。我们的目标是针对实践中纵向调查中的流失调整方法制定具体建议。

方法

我们分析了来自美国全国监测未来小组研究的四组个体(年龄在 18 至 29/30 岁之间)的数据,系统比较了使用各种物质使用结果分析纵向数据的替代方法,并研究了关于物质使用流行率和轨迹的推论对使用方法的敏感性,因为这取决于大学入学情况。

结果

我们的结果表明,在每个波中分析所有可用的观察值,同时考虑到重复观察、样本选择和流失之间的相关性,是最有效的方法。调整效果在特定波的描述性估计中很明显,但在协变量调整的轨迹建模中通常较小。

结论

这些调整可以提高我们关于年轻人物质使用轨迹的发现的准确性,在一定程度上可以改进这些发现的意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/065f/9464329/ac369478bcd9/MPR-31-e1916-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/065f/9464329/19656d3f2815/MPR-31-e1916-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/065f/9464329/04830c982b8e/MPR-31-e1916-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/065f/9464329/e297fae161ea/MPR-31-e1916-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/065f/9464329/ca034244f517/MPR-31-e1916-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/065f/9464329/2ee8867f75bd/MPR-31-e1916-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/065f/9464329/4f7f832be28d/MPR-31-e1916-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/065f/9464329/a0dfc4133d76/MPR-31-e1916-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/065f/9464329/ac369478bcd9/MPR-31-e1916-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/065f/9464329/19656d3f2815/MPR-31-e1916-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/065f/9464329/04830c982b8e/MPR-31-e1916-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/065f/9464329/e297fae161ea/MPR-31-e1916-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/065f/9464329/ca034244f517/MPR-31-e1916-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/065f/9464329/2ee8867f75bd/MPR-31-e1916-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/065f/9464329/4f7f832be28d/MPR-31-e1916-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/065f/9464329/a0dfc4133d76/MPR-31-e1916-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/065f/9464329/ac369478bcd9/MPR-31-e1916-g005.jpg

相似文献

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
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.
3
Trajectories of risk behaviors across adolescence and young adulthood: The role of race and ethnicity.青少年到成年早期风险行为轨迹:种族和民族的作用。
Addict Behav. 2018 Jan;76:1-7. doi: 10.1016/j.addbeh.2017.07.014. Epub 2017 Jul 15.
4
Comparison of a web-push survey research protocol with a mailed paper and pencil protocol in the Monitoring the Future panel survey.网络推送调查研究方案与邮寄纸质和铅笔问卷方案在“监测未来”面板调查中的比较。
Addiction. 2021 Jan;116(1):191-199. doi: 10.1111/add.15158. Epub 2020 Jul 8.
5
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.
6
Trajectories of Prescription Drug Misuse Among US Adults From Ages 18 to 50 Years.美国 18 至 50 岁成年人处方药滥用轨迹。
JAMA Netw Open. 2022 Jan 4;5(1):e2141995. doi: 10.1001/jamanetworkopen.2021.41995.
7
Association between adolescent substance use and obesity in young adulthood: a group-based dual trajectory analysis.青少年时期物质使用与成年早期肥胖的关系:基于群组的双重轨迹分析。
Addict Behav. 2013 Nov;38(11):2653-60. doi: 10.1016/j.addbeh.2013.06.024. Epub 2013 Jul 3.
8
Substance use and exercise participation among young adults: parallel trajectories in a national cohort-sequential study.年轻人的物质使用与运动参与:一项全国队列序贯研究中的平行轨迹。
Addiction. 2011 Oct;106(10):1855-65; discussion 1866-7. doi: 10.1111/j.1360-0443.2011.03489.x. Epub 2011 Jun 24.
9
Alcohol, marijuana, and tobacco use trajectories from age 12 to 24 years: demographic correlates and young adult substance use problems.12至24岁期间酒精、大麻和烟草的使用轨迹:人口统计学关联因素与青年成人物质使用问题
Dev Psychopathol. 2015 Feb;27(1):253-77. doi: 10.1017/S0954579414000650. Epub 2014 Jul 14.
10
Trajectories of energy drink consumption and subsequent drug use during young adulthood.青年期能量饮料消费及随后药物使用的轨迹。
Drug Alcohol Depend. 2017 Oct 1;179:424-432. doi: 10.1016/j.drugalcdep.2017.06.008. Epub 2017 Aug 8.

引用本文的文献

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
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.
3
Longitudinal associations of e-cigarette use with cigarette, marijuana, and other drug use initiation among US adolescents and young adults: Findings from the population assessment of tobacco and health study (Waves 1-6).

本文引用的文献

1
Multiple Imputation with Massive Data: An Application to the Panel Study of Income Dynamics.海量数据的多重插补:在收入动态面板研究中的应用
J Surv Stat Methodol. 2021 Oct 19;11(1):260-283. doi: 10.1093/jssam/smab038. eCollection 2023 Feb.
2
Bayesian profiling multiple imputation for missing hemoglobin values in electronic health records.电子健康记录中血红蛋白值缺失的贝叶斯轮廓多重填补法
Ann Appl Stat. 2020 Dec;14(4):1903-1924. doi: 10.1214/20-AOAS1378. Epub 2020 Dec 19.
3
Key Subgroup Differences in Age-Related Change From 18 to 55 in Alcohol and Marijuana Use: U.S. National Data.
电子烟使用与美国青少年和年轻人开始使用香烟、大麻和其他毒品之间的纵向关联:来自全国烟草和健康评估研究(第 1-6 波)的结果。
Drug Alcohol Depend. 2024 Oct 1;263:111402. doi: 10.1016/j.drugalcdep.2024.111402. Epub 2024 Jul 26.
4
Individual and Community level Developmental Adversities: Associations with Marijuana and Alcohol Use in Late-Adolescents and Young Adults.个体和社区层面的发育逆境:与青少年晚期和年轻成年人的大麻和酒精使用的关联。
J Youth Adolesc. 2024 Apr;53(4):799-813. doi: 10.1007/s10964-023-01881-9. Epub 2023 Oct 17.
5
Comparisons of statistical methods for handling attrition in a follow-up visit with complex survey sampling.比较处理随访中复杂抽样调查数据缺失的统计方法。
Stat Med. 2023 May 20;42(11):1641-1668. doi: 10.1002/sim.9692. Epub 2023 Mar 7.
6
Non-daily Cigarette Smoking: Stability and Transition to Abstinence in Young Adults.非每日吸烟:年轻人的稳定性和向戒烟的转变。
Nicotine Tob Res. 2023 Jan 1;25(1):151-158. doi: 10.1093/ntr/ntac189.
18 岁至 55 岁期间,酒精和大麻使用的年龄相关变化的关键亚组差异:美国国家数据。
J Stud Alcohol Drugs. 2021 Jan;82(1):93-102. doi: 10.15288/jsad.2021.82.93.
4
When does attrition lead to biased estimates of alcohol consumption? Bias analysis for loss to follow-up in 30 longitudinal cohorts.当损耗导致对酒精消费的有偏估计时会怎样?30 个纵向队列中失访的偏差分析。
Int J Methods Psychiatr Res. 2020 Dec;29(4):1-9. doi: 10.1002/mpr.1842. Epub 2020 Jul 13.
5
Trajectories of prescription drug misuse during the transition from late adolescence into adulthood in the USA: a national longitudinal multicohort study.美国从青少年晚期到成年期过渡阶段的处方药滥用轨迹:一项全国性纵向多队列研究
Lancet Psychiatry. 2019 Oct;6(10):840-850. doi: 10.1016/S2215-0366(19)30299-8. Epub 2019 Sep 11.
6
Cohort Profile: The National Longitudinal Study of Adolescent to Adult Health (Add Health).队列简介:青少年到成人健康的全国纵向研究(“加健康”研究)
Int J Epidemiol. 2019 Oct 1;48(5):1415-1415k. doi: 10.1093/ije/dyz115.
7
DSM-5 substance use disorders among college-age young adults in the United States: Prevalence, remission and treatment.DSM-5 物质使用障碍在美国青年中的流行情况、缓解情况和治疗情况。
J Am Coll Health. 2020 Aug-Sep;68(6):650-657. doi: 10.1080/07448481.2019.1590368. Epub 2019 Apr 4.
8
Shifting Age of Peak Binge Drinking Prevalence: Historical Changes in Normative Trajectories Among Young Adults Aged 18 to 30.峰值 binge drinking 流行率的年龄转移:18 至 30 岁年轻人的规范轨迹的历史变化。
Alcohol Clin Exp Res. 2019 Feb;43(2):287-298. doi: 10.1111/acer.13933. Epub 2019 Jan 15.
9
Young adult longitudinal patterns of marijuana use among US National samples of 12th grade frequent marijuana users: a repeated-measures latent class analysis.美国 12 年级经常使用大麻的学生全国样本中,青年成年人的大麻使用纵向模式:重复测量潜在类别分析。
Addiction. 2019 Jun;114(6):1035-1048. doi: 10.1111/add.14548. Epub 2019 Jan 27.
10
College degree attainment by age of first marijuana use and parental education.首次使用大麻年龄与父母受教育程度和大学学位获得情况的关系。
Subst Abus. 2019;40(1):66-70. doi: 10.1080/08897077.2018.1521354. Epub 2018 Nov 26.