ASYMPTOTIC ROBUSTNESS STUDY OF THE POLYCHORIC CORRELATION ESTIMATION

作者：Jin Shaobo^*; Yang Wallentin Fan

来源：Psychometrika, 2017, 82(1): 67-85.

DOI：10.1007/s11336-016-9512-2

• underlying distribution
• asymptotic covariance matrix
• non-normality
• pseudo-maximum likelihood

Asymptotic robustness against misspecification of the underlying distribution for the polychoric correlation estimation is studied. The asymptotic normality of the pseudo-maximum likelihood estimator is derived using the two-step estimation procedure. The t distribution assumption and the skew-normal distribution assumption are used as alternatives to the normal distribution assumption in a numerical study. The numerical results show that the underlying normal distribution can be substantially biased, even though skewness and kurtosis are not large. The skew-normal assumption generally produces a lower bias than the normal assumption. Thus, it is worth using a non-normal distributional assumption if the normal assumption is dubious.

• 出版日期2017-3