评论斯图尔等人的文章：在建立时变趋势模型时考虑个体特定的异质性。
Commentary on Stull et al.: Considering person-specific heterogeneity when modeling time-varying trends.
机构信息
Department of Psychology, University of Washington, Seattle, WA, USA.
Department of Global Health, University of Washington, Seattle, WA, USA.
出版信息
Addiction. 2023 Nov;118(11):2233-2234. doi: 10.1111/add.16308. Epub 2023 Aug 8.
Abstract
TVEM represents an important statistical method for modeling non-linear, dynamic processes. However, TVEM models the -level process for the focal effect. As addiction- and recovery-related processes demonstrate person-specific heterogeneity, we encourage researchers to model non-parametric non-ergodic change to advance our understanding of how, when, and for whom change occurs.
摘要
TVEM 是一种用于建模非线性、动态过程的重要统计方法。然而，TVEM 模型化了焦点效应的 - 水平过程。由于成瘾和恢复相关的过程表现出个体特异性的异质性，我们鼓励研究人员对非参数、非遍历性的变化进行建模，以深入了解变化发生的方式、时间和对象。
相似文献
1
Commentary on Stull et al.: Considering person-specific heterogeneity when modeling time-varying trends.评论斯图尔等人的文章：在建立时变趋势模型时考虑个体特定的异质性。
Addiction. 2023 Nov;118(11):2233-2234. doi: 10.1111/add.16308. Epub 2023 Aug 8.
2
Time-varying effect modeling with intensive longitudinal data: Examining dynamic links among craving, affect, self-efficacy and substance use during addiction recovery.基于密集纵向数据的时变效应建模：在成瘾康复过程中考察渴求、情感、自我效能与物质使用之间的动态关联。
Addiction. 2023 Nov;118(11):2220-2232. doi: 10.1111/add.16284. Epub 2023 Jul 7.
3
Testing the cross-applicability of juvenile sex estimation from diaphyseal dimensions.测试骨干尺寸在青少年性别估计中的跨适用性。
Forensic Sci Int. 2021 Apr;321:110739. doi: 10.1016/j.forsciint.2021.110739. Epub 2021 Feb 20.
4
Relocation of McCammon & Stull, 1978 (Annelida, Capitellidae) in Fauchald, 1972.麦卡蒙和斯图尔（1978年，环节动物门， Capitellidae科）于1972年在福查尔德的重新分类。
Zookeys. 2017 Nov 21(715):93-101. doi: 10.3897/zookeys.715.13936. eCollection 2017.
6
Apples and oranges in the basket of a clinical model for exercise addiction: Rebuttal to Brevers et al. (2022).筐中的苹果和橙子：对 Brevers 等人（2022 年）的反驳。临床运动成瘾模型
J Behav Addict. 2022 Jun 1;11(2):240-242. doi: 10.1556/2006.2022.00036. Print 2022 Jul 13.
7
Invited commentary: Taking advantage of time-varying neighborhood environments.特邀评论：利用时变的邻里环境。
Am J Epidemiol. 2014 Sep 1;180(5):462-6. doi: 10.1093/aje/kwu170. Epub 2014 Aug 11.
8
The Richard J. Stull Commentary: the corporatization of values.
Rep Natl Forum Hosp Health Aff. 1984:49-55.
9
Discussing evidence on the components model of addiction. A commentary on Fournier et al. (2023).探讨成瘾的成分模型的证据。对 Fournier 等人（2023 年）的评论。
Addict Behav. 2023 Oct;145:107764. doi: 10.1016/j.addbeh.2023.107764. Epub 2023 Jun 8.
10
Moving beyond the "eating addiction" versus "food addiction" debate: Comment on Schulte et al. (2017).超越“饮食成瘾”与“食物成瘾”的争论：评 Schulte 等人（2017 年）的观点。
Appetite. 2018 Nov 1;130:286-292. doi: 10.1016/j.appet.2018.06.025. Epub 2018 Jun 21.
本文引用的文献
1
Unlocking nonlinear dynamics and multistability from intensive longitudinal data: A novel method.从密集纵向数据中解锁非线性动力学和多重稳定性：一种新方法。
Psychol Methods. 2023 Dec 14. doi: 10.1037/met0000623.
2
Time-varying effect modeling with intensive longitudinal data: Examining dynamic links among craving, affect, self-efficacy and substance use during addiction recovery.基于密集纵向数据的时变效应建模：在成瘾康复过程中考察渴求、情感、自我效能与物质使用之间的动态关联。
Addiction. 2023 Nov;118(11):2220-2232. doi: 10.1111/add.16284. Epub 2023 Jul 7.
3
Pooled and person-specific machine learning models for predicting future alcohol consumption, craving, and wanting to drink: A demonstration of parallel utility.用于预测未来酒精消费、渴望饮酒和饮酒意愿的汇总及个性化机器学习模型：并行效用的演示。
Psychol Addict Behav. 2022 May;36(3):296-306. doi: 10.1037/adb0000666. Epub 2021 Apr 22.
4
Advancing statistical analysis of ambulatory assessment data in the study of addictive behavior: A primer on three person-oriented techniques.推进成瘾行为研究中动态评估数据的统计分析：三种个体导向技术简介。
Addict Behav. 2018 Aug;83:25-34. doi: 10.1016/j.addbeh.2017.12.018. Epub 2017 Dec 15.
5
Modeling the complexity of post-treatment drinking: it's a rocky road to relapse.模拟治疗后饮酒的复杂性：复发之路崎岖坎坷。
Clin Psychol Rev. 2007 Jul;27(6):724-38. doi: 10.1016/j.cpr.2007.01.002. Epub 2007 Jan 18.
Zotero 插件