Velicer Wayne F, Cumming Geoff, Fava Joseph L, Rossi Joseph S, Prochaska James O, Johnson Janet
Cancer Prevention Research Center, University of Rhode Island, USA.
Appl Psychol. 2008 Oct;57(4):589-608. doi: 10.1111/j.1464-0597.2008.00348.x. Epub 2008 Jul 8.
Traditional Null Hypothesis Testing procedures are poorly adapted to theory testing. The methodology can mislead researchers in several ways, including: (a) a lack of power can result in an erroneous rejection of the theory; (b) the focus on directionality (ordinal tests) rather than more precise quantitative predictions limits the information gained; and (c) the misuse of probability values to indicate effect size. An alternative approach is proposed which involves employing the theory to generate explicit effect size predictions that are compared to the effect size estimates and related confidence intervals to test the theoretical predictions. This procedure is illustrated employing the Transtheoretical Model. Data from a sample (N = 3,967) of smokers from a large New England HMO system were used to test the model. There were a total of 15 predictions evaluated, each involving the relation between Stage of Change and one of the other 15 Transtheoretical Model variables. For each variable, omega-squared and the related confidence interval were calculated and compared to the predicted effect sizes. Eleven of the 15 predictions were confirmed, providing support for the theoretical model. Quantitative predictions represent a much more direct, informative, and strong test of a theory than the traditional test of significance.
传统的零假设检验程序不太适合理论检验。该方法可能会在几个方面误导研究人员，包括：(a) 检验效能不足可能导致对理论的错误否定；(b) 关注方向性（顺序检验）而非更精确的定量预测会限制所获得的信息；以及 (c) 错误地使用概率值来表示效应大小。本文提出了一种替代方法，该方法涉及运用理论来生成明确的效应大小预测，并将其与效应大小估计值及相关的置信区间进行比较，以检验理论预测。运用跨理论模型对这一程序进行了说明。来自新英格兰地区一个大型健康维护组织（HMO）系统的3967名吸烟者样本的数据被用于检验该模型。总共评估了15个预测，每个预测都涉及改变阶段与跨理论模型中其他15个变量之一之间的关系。对于每个变量，计算了ω²及相关的置信区间，并与预测的效应大小进行比较。15个预测中有11个得到了证实，为该理论模型提供了支持。与传统的显著性检验相比，定量预测对理论的检验更加直接、信息丰富且有力。
