Falkenström Fredrik, Finkel Steven, Sandell Rolf, Rubel Julian A, Holmqvist Rolf
Centre for Psychotherapy Research and Education, Karolinska Institutet.
Department of Political Science, University of Pittsburgh.
J Consult Clin Psychol. 2017 Jun;85(6):537-549. doi: 10.1037/ccp0000203. Epub 2017 Apr 10.
There is a need for rigorous methods to study the mechanisms that lead to individual-level change (i.e., process-outcome research). We argue that panel data (i.e., longitudinal study of a number of individuals) methods have 3 major advantages for psychotherapy researchers: (1) enabling microanalytic study of psychotherapeutic processes in a clinically intuitive way, (2) modeling lagged associations over time to ensure direction of causality, and (3) isolating within-patient changes over time from between-patient differences, thereby protecting against confounding influences because of the effects of unobserved stable attributes of individuals. However, dynamic panel data methods present a complex set of analytical challenges. We focus on 2 particular issues: (1) how long-term trajectories in the variables of interest over the study period should be handled, and (2) how the use of a lagged dependent variable as a predictor in regression-based dynamic panel models induces endogeneity (i.e., violation of independence between predictor and model error term) that must be taken into account in order to appropriately isolate within- and between-person effects.
An example from a study of working alliance in psychotherapy in primary care in Sweden is used to illustrate some of these analytic decisions and their impact on parameter estimates.
Estimates were strongly influenced by the way linear trajectories were handled; that is, whether variables were "detrended" or not.
The issue of when detrending should be done is discussed, and recommendations for research are provided. (PsycINFO Database Record
需要采用严谨的方法来研究导致个体层面变化的机制（即过程-结果研究）。我们认为，面板数据（即对若干个体的纵向研究）方法对心理治疗研究人员具有3个主要优势：（1）能够以临床直观的方式对心理治疗过程进行微观分析研究；（2）对随时间变化的滞后关联进行建模，以确保因果关系的方向；（3）将个体随时间的内部变化与个体间差异区分开来，从而防范因个体未观察到的稳定属性的影响而产生的混杂影响。然而，动态面板数据方法带来了一系列复杂的分析挑战。我们关注两个特定问题：（1）在研究期间应如何处理感兴趣变量的长期轨迹；（2）在基于回归的动态面板模型中使用滞后因变量作为预测变量如何引发内生性（即预测变量与模型误差项之间独立性的违反），为了适当地分离个体内部和个体间效应，必须考虑这一点。
以瑞典初级保健中心理治疗工作联盟研究的一个例子来说明其中一些分析决策及其对参数估计的影响。
估计值受到处理线性轨迹方式的强烈影响；也就是说，变量是否进行了“去趋势化”处理。
讨论了何时应进行去趋势化处理的问题，并为研究提供了建议。（《心理学文摘数据库记录》
