Baldwin Scott A, Imel Zac E, Braithwaite Scott R, Atkins David C
Department of Psychology, Brigham Young University.
Department of Educational Psychology, University of Utah.
J Consult Clin Psychol. 2014 Oct;82(5):920-30. doi: 10.1037/a0035628. Epub 2014 Feb 3.
Multilevel models have become a standard data analysis approach in intervention research. Although the vast majority of intervention studies involve multiple outcome measures, few studies use multivariate analysis methods. The authors discuss multivariate extensions to the multilevel model that can be used by psychotherapy researchers.
Using simulated longitudinal treatment data, the authors show how multivariate models extend common univariate growth models and how the multivariate model can be used to examine multivariate hypotheses involving fixed effects (e.g., does the size of the treatment effect differ across outcomes?) and random effects (e.g., is change in one outcome related to change in the other?). An online supplemental appendix provides annotated computer code and simulated example data for implementing a multivariate model.
Multivariate multilevel models are flexible, powerful models that can enhance clinical research.
多层模型已成为干预研究中的标准数据分析方法。尽管绝大多数干预研究涉及多个结局指标，但很少有研究使用多变量分析方法。作者讨论了心理治疗研究人员可使用的多层模型的多变量扩展。
作者使用模拟的纵向治疗数据，展示了多变量模型如何扩展常见的单变量增长模型，以及多变量模型如何用于检验涉及固定效应（例如，治疗效果的大小在不同结局之间是否不同？）和随机效应（例如，一个结局的变化与另一个结局的变化是否相关？）的多变量假设。一个在线补充附录提供了用于实现多变量模型的带注释的计算机代码和模拟示例数据。
多变量多层模型是灵活、强大的模型，可增强临床研究。
