4.4 Article

Is the ML chi-square ever robust to nonnormality? A cautionary note with missing data

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Mathematics, Interdisciplinary Applications

A statistically justified pairwise ML method for incomplete nonnormal data: A comparison with direct ML and pairwise ADF

V Savalei et al.

STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL (2005)

Article Mathematics, Interdisciplinary Applications

Tests of homogeneity of means and covariance matrices for multivariate incomplete data

KH Kim et al.

PSYCHOMETRIKA (2002)

Article Mathematics, Interdisciplinary Applications

A Primer on Maximum Likelihood Algorithms Available for Use With Missing Data

Craig K. Enders

STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL (2001)

Article Mathematics, Interdisciplinary Applications

The Relative Performance of Full Information Maximum Likelihood Estimation for Missing Data in Structural Equation Models

Craig K. Enders et al.

STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL (2001)