Interpreting the Likelihood Ratio Statistic in Factor Models when Sample Size is Small
通过蒙特卡洛实验发现，当常规条件满足且样本量至少为30时，渐近理论适用；否则在所有样本量下都可能产生误导。
Abstract The use of the likelihood ratio statistic in testing the goodness of fit of the exploratory factor model has no formal justification when, as is often the case in practice, the usual regularity conditions are not met. In a Monte Carlo experiment it is found that the asymptotic theory seems to be appropriate when the regularity conditions obtain and sample size is at least 30. When the regularity conditions are not satisfied, the asymptotic theory seems to be misleading in all sample sizes considered.