Common Factor Score Estimates in Multiple Regression Problems
研究了在回归问题中将共同因子作为自变量时，不同因子得分估计方法的优劣，蒙特卡洛模拟表明Dwyer因子扩展法整体效果最佳。
The issue of alternative methods for estimating factor scores is raised and, in particular, the case of using common factors as independent variables in regression problems is singled out for investigation. A Monté Carlo simulation experiment (varying: factor scoring method, uniqueness, assumption about factor correlations, and number of observed variables factored) is reported. Though several factor score estimators perform “equivalently” in the simulation, the best overall results are obtained with the Dwyer factor extension technique.