Covariance Structure Model Fit Testing Under Missing Data: An Application of the Supplemented EM Algorithm
Author:
Affiliation:
1. a Graduate School of Education and Information Studies , University of California , Los Angeles
2. b L. L. Thurstone Psychometric Lab , University of North Carolina
Publisher
Informa UK Limited
Subject
Arts and Humanities (miscellaneous),Experimental and Cognitive Psychology,General Medicine,Statistics and Probability
Link
https://www.tandfonline.com/doi/pdf/10.1080/00273170902794255
Reference24 articles.
1. Missing Data Techniques for Structural Equation Modeling.
2. Maximum Likelihood Estimates for a Multivariate Normal Distribution when Some Observations are Missing
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