Ferrer Emilio, Balluerka Nekane, Widaman Keith F
Department of Psychology, University of California, Davis.
Methodology (Gott). 2008;4(1):22-36. doi: 10.1027/1614-2241.4.1.22.
Latent growth modeling has been a topic of intense interest during the past two decades. Most theoretical and applied work has employed first-order growth models, in which a single manifest variable serves as indicator of trait level at each time of measurement. In the current paper, we concentrate on issues regarding second-order growth models, which have multiple indicators at each time of measurement. With multiple indicators, tests of factorial invariance of parameters across times of measurement can be tested. We conduct such tests using two sets of data, which differ in the extent to which factorial invariance holds, and evaluate longitudinal confirmatory factor, latent growth curve, and latent difference score models. We demonstrate that, if factorial invariance fails to hold, choice of indicator used to identify the latent variable can have substantial influences on the characterization of patterns of growth, strong enough to alter conclusions about growth. We also discuss matters related to the scaling of growth factors and conclude with recommendations for practice and for future research.
在过去二十年中，潜在增长模型一直是一个备受关注的话题。大多数理论和应用研究都采用一阶增长模型，其中单一的显性变量作为每次测量时特质水平的指标。在本文中，我们关注二阶增长模型的相关问题，该模型在每次测量时有多个指标。有了多个指标，就可以检验跨测量时间的参数因子不变性。我们使用两组数据进行此类检验，这两组数据在因子不变性成立的程度上有所不同，并评估纵向验证性因子、潜在增长曲线和潜在差异得分模型。我们证明，如果因子不变性不成立，用于识别潜在变量的指标选择可能会对增长模式的表征产生重大影响，其影响程度足以改变关于增长的结论。我们还讨论了与增长因子缩放相关的问题，并以对实践和未来研究的建议作为结论。
