Thomas Philipp, Rammsayer Thomas, Schweizer Karl, Troche Stefan
University of Bern, Department of Psychology and Center for Cognition, Learning and Memory.
Johann Wolfgang Goethe University Frankfurt, Department of Psychology.
Adv Cogn Psychol. 2015 Mar 31;11(1):3-13. doi: 10.5709/acp-0166-6. eCollection 2015.
Numerous studies reported a strong link between working memory capacity (WMC) and fluid intelligence (Gf), although views differ in respect to how close these two constructs are related to each other. In the present study, we used a WMC task with five levels of task demands to assess the relationship between WMC and Gf by means of a new methodological approach referred to as fixed-links modeling. Fixed-links models belong to the family of confirmatory factor analysis (CFA) and are of particular interest for experimental, repeated-measures designs. With this technique, processes systematically varying across task conditions can be disentangled from processes unaffected by the experimental manipulation. Proceeding from the assumption that experimental manipulation in a WMC task leads to increasing demands on WMC, the processes systematically varying across task conditions can be assumed to be WMC-specific. Processes not varying across task conditions, on the other hand, are probably independent of WMC. Fixed-links models allow for representing these two kinds of processes by two independent latent variables. In contrast to traditional CFA where a common latent variable is derived from the different task conditions, fixed-links models facilitate a more precise or purified representation of the WMC-related processes of interest. By using fixed-links modeling to analyze data of 200 participants, we identified a non-experimental latent variable, representing processes that remained constant irrespective of the WMC task conditions, and an experimental latent variable which reflected processes that varied as a function of experimental manipulation. This latter variable represents the increasing demands on WMC and, hence, was considered a purified measure of WMC controlled for the constant processes. Fixed-links modeling showed that both the purified measure of WMC (β = .48) as well as the constant processes involved in the task (β = .45) were related to Gf. Taken together, these two latent variables explained the same portion of variance of Gf as a single latent variable obtained by traditional CFA (β = .65) indicating that traditional CFA causes an overestimation of the effective relationship between WMC and Gf. Thus, fixed-links modeling provides a feasible method for a more valid investigation of the functional relationship between specific constructs.
众多研究报告了工作记忆容量(WMC)与流体智力(Gf)之间存在紧密联系,尽管对于这两个概念彼此之间的关联程度,各方观点有所不同。在本研究中,我们使用了一个具有五个任务需求水平的WMC任务,通过一种称为固定链接建模的新方法来评估WMC与Gf之间的关系。固定链接模型属于验证性因素分析(CFA)家族,对于实验性重复测量设计尤为重要。使用这种技术,可以将在不同任务条件下系统变化的过程与不受实验操作影响的过程区分开来。基于WMC任务中的实验操作会导致对WMC的需求增加这一假设,在不同任务条件下系统变化的过程可被假定为特定于WMC的过程。另一方面,在不同任务条件下不变的过程可能与WMC无关。固定链接模型允许通过两个独立的潜在变量来表示这两种过程。与传统CFA不同,传统CFA从不同任务条件中导出一个共同的潜在变量,而固定链接模型有助于更精确或纯净地表示感兴趣的与WMC相关的过程。通过使用固定链接建模分析200名参与者的数据,我们确定了一个非实验性潜在变量,它代表了无论WMC任务条件如何都保持不变的过程,以及一个实验性潜在变量,它反映了随实验操作而变化的过程。后一个变量代表了对WMC不断增加的需求,因此被视为针对恒定过程进行控制的WMC的纯净度量。固定链接建模表明,WMC的纯净度量(β = 0.48)以及任务中涉及的恒定过程(β = 0.45)都与Gf相关。综上所述,这两个潜在变量解释的Gf方差部分与通过传统CFA获得的单个潜在变量(β = 0.65)相同,这表明传统CFA高估了WMC与Gf之间的有效关系。因此,固定链接建模为更有效地研究特定概念之间的功能关系提供了一种可行的方法。