Analytic approaches for assessing long-term treatment effects - Examples of empirical applications and findings
Analytic approaches for assessing long-term treatment effects - Examples of empirical applications and findings
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DOI：
10.1177/0193841x0102500206
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发表时间：
2001-04-01
影响因子：
0.9
通讯作者：
Anglin, MD
中科院分区：
文献类型：
--
作者：
Hser, YI;Shen, HK;Anglin, MD
讨论了分析方法，包括结构方程模型（自回归面板模型）、分层线性模型、潜在增长曲线模型、生存/事件历史分析、潜在转变模型和时间序列分析（间断时间序列、多元时间序列分析），讨论它们对不同结构数据的适用性及其在评估治疗时间效应中的效用。通过介绍先前研究中检查治疗效果的时间模式的各种方法的应用来说明方法。这些纵向建模方法和随附的计算机软件开发的最新进展为通过具有不同数量和评估间隔以及测量类型的纵向数据检查长期治疗效果提供了巨大的灵活性。多方法评估将有助于更全面地了解长期药物滥用过程及其治疗的复杂现象。
Analytic approaches, including the structural equation model (autoregressive panel model), hierarchical linear model, latent growth curve model, survival/event history analysis, latent transition model, and time-series analysis (interrupted time series, multivariate time-series analysis) are discussed for their applicability to data of different structures and their utility in evaluating temporal effects of treatment. Methods are illustrated by presenting applications of the various approaches in previous studies examining temporal patterns of treatment effects. Recent advancements in these longitudinal modeling approaches and the accompanying computer software development offer tremendous flexibility in examining long-term treatment effects through longitudinal data with varying numbers and intervals of assessment and types of measures. A multimethod assessment will contribute to a more complete understanding of the complex phenomena of the long-term courses of substance use and its treatment.