Ullrich Johannes, Schermelleh-Engel Karin, Böttcher Björn
Department of Psychology, Goethe University, Frankfurt am Main, Germany.
J Pers Soc Psychol. 2008 Oct;95(4):774-94. doi: 10.1037/a0012709.
Ambivalence researchers often collapse separate measures of positivity and negativity into a single numerical index of ambivalence and refer to it as objective, operative, or potential ambivalence. The authors argue that this univariate approach to ambivalence models undermines the validity of subsequent statistical analyses because it confounds the effects of the index and its components. To remedy this situation, they demonstrate how the assumptions underlying the indices derived from the conflicting reactions model and similarity-intensity model can be tested using a multivariate approach to ambivalence models. On the basis of computer simulations and reanalyses of published moderator effects, the authors show that the frequently reported moderating influence of ambivalence on attitude effects may be a statistical artifact resulting from unmodeled correlations of positivity and negativity with attitude and the dependent variable. On the basis of extensive power analyses, they conclude that it may be extremely difficult to detect moderator effects of ambivalence in observational data. Therefore, they encourage ambivalence researchers to take an experimental approach to study design and a multivariate approach to data analysis.
矛盾心理研究者常常将积极和消极的单独测量合并为一个单一的矛盾心理数值指标，并将其称为客观、有效或潜在的矛盾心理。作者认为，这种对矛盾心理模型的单变量方法破坏了后续统计分析的有效性，因为它混淆了该指标及其组成部分的影响。为了纠正这种情况，他们展示了如何使用矛盾心理模型的多变量方法来检验源自冲突反应模型和相似性-强度模型的指标所基于的假设。基于计算机模拟和对已发表的调节效应的重新分析，作者表明，经常报道的矛盾心理对态度效应的调节影响可能是一种统计假象，这是由积极和消极与态度及因变量的未建模相关性导致的。基于广泛的功效分析，他们得出结论，在观测数据中检测矛盾心理的调节效应可能极其困难。因此，他们鼓励矛盾心理研究者采用实验方法进行研究设计，并采用多变量方法进行数据分析。
