Pardo Antonio, Garrido Jesús, Ruiz Miguel A, San Martín Rafael
Universidad Autónoma de Madrid.
Psicothema. 2007 May;19(2):343-9.
Although interaction in analysis of variance has an unequivocal theoretical meaning (and so it appears in the statistic literature), frequent misconceptions are found in empirical research, which, in many cases, lead to wrong conclusions. In this paper, 150 articles are reviewed: in 12.7% of them, no attention is paid to the interaction (either because it is not analysed or because it is analysed but not discussed); in 79.1%, interaction is studied through simple effects analysis; and only in 8.2% of the cases, interaction is correctly discussed. It could be that psychology researchers tend to analyse and interpret the interaction between factors incorrectly because the most widespread statistic packages (with SPSS in the lead) do not allow performing the comparisons needed to analyse a significant interaction in factorial designs with randomized groups. In order to contribute to eradicating this problem, we herein show how to design some of the linear comparisons that allow isolating the interaction effect, and we explain how to use SPSS to compute these comparisons.
尽管方差分析中的交互作用有着明确的理论意义（因此它出现在统计学文献中），但在实证研究中却经常发现误解，在许多情况下，这些误解会导致错误的结论。本文回顾了150篇文章：其中12.7%未关注交互作用（要么未进行分析，要么虽进行了分析但未讨论）；79.1%通过简单效应分析来研究交互作用；只有8.2%的情况对交互作用进行了正确的讨论。可能是因为最广泛使用的统计软件包（以SPSS为首）不允许进行在随机分组的析因设计中分析显著交互作用所需的比较，心理学研究人员倾向于错误地分析和解释因素之间的交互作用。为了有助于消除这个问题，我们在此展示如何设计一些线性比较以分离出交互效应，并解释如何使用SPSS来计算这些比较。
