STATISTICAL POWER AND COST IN TRAINING EVALUATION: SOME NEW CONSIDERATIONS
研究了两种降低培训评估成本的方法：通过不等组分配和采用代理指标，在保持统计功效的同时优化成本，并给出了最优组分配比例和代理指标的成本权衡方法。
Two ways to reduce the costs of training evaluation are examined. First, we examine the potential for reducing the costs of training evaluation by assigning different numbers of subjects into training and control groups. Given a total N of subjects, statistical power to detect the effectiveness of a training program can be maximized by assigning the subjects equally to training and control groups. If we take into account the costs of training evaluation, however, an unequal‐group‐size design with a larger total N may achieve the same level of statistical power at lower cost. We derive formulas for the optimal ratios of the control group size to the training group size for both ANOVA and ANCOVA designs, incorporating the differential costs of training and control group participation. Second, we examine the possibility that using a less expensive proxy criterion measure in place of the target criterion measure of interest when evaluating the training effectiveness can pay off. We show that using a proxy criterion increases the sample size needed to achieve a given level of statistical power, and then we describe procedures for examining the tradeoff between the costs saved by using the less expensive proxy criterion and the costs incurred by the larger sample size.