Bias correction of the Akaike information criterion in factor analysis

JOURNAL OF MULTIVARIATE ANALYSIS

卷:149

Article

Ogasawara, Haruhiko¹ 

[1] Otaru Univ, Dept Informat & Management Sci, 3-5-21 Midori, Otaru, Hokkaido 0478501, Japan

关键词: Asymptotic bias;    AIC;    Covariance structure analysis;    Exploratory factor analysis;    Non-normality;   

DOI  :  10.1016/j.jmva.2016.04.003

来源: Elsevier

【 摘 要 】

The higher-order asymptotic bias for the Akaike information criterion (AIC) in factor analysis or covariance structure analysis is obtained when the parameter estimators are given by the Wishart maximum likelihood. Since the formula of the exact higher-order bias is complicated, simple approximations which do not include unknown parameter values are obtained. Numerical examples with simulations show that the approximations are reason ably similar to their corresponding exact asymptotic values and simulated values. Simulations for model selection give consistently improved results by the approximate correction of the higher-order bias for the AIC over the usual AIC. (C) 2016 Elsevier Inc. All rights reserved.

【 授权许可】

Free