THE PREDICTIVE ABILITY CRITERION IN EXPERIMENTAL JUDGMENT RESEARCH IN ACCOUNTING*
指出，会计实验判断研究中常用方差解释比例来评估线性模型的预测能力，但该统计量受实验设计影响，高相关可能不代表模型成功，建议补充定性检验。
ABSTRACT Previous experimental judgment research in accounting has been interpreted as supportive of the linear model as an appropriate representation of decision‐making behavior in nearly all of the tasks investigated. Moreover, nonlinear models have come to be viewed as adding relatively little predictive power over that provided by the linear model, even in tasks considered to be inherently nonlinear. These conclusions were based largely upon evaluating the predictive ability of the linear model in terms of statistics measuring the proportion of variance accounted for by the model. In the present paper it is argued that, since these statistics are not independent of the experimental design, it is not clear whether the high correlations are indicative of the model's success in representing decision‐making processes or instead are more the result of various features of the experimental design. It is suggested that correlational tests be supplemented with qualitative tests of the predictive ability of a model. Implications for accounting are discussed.