title: Maximum likelihood estimation in covariance structure analysis with truncated data.
abstract: We study an estimation procedure for maximum likelihood estimation in covariance structure analysis with truncated data, and obtain the statistical properties of the estimator as well as a test of the model structure. Truncated data with and without knowledge about the number of unmeasured observations are both considered. The Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm, which requires only first derivatives, is proposed to obtain the maximum likelihood estimates. We illustrate the statistics and parameter estimates by a fictitious example. The maximum likelihood method is compared to an alternative two-stage method.
authors.affiliation: Department of Statistics, Chinese University of Hong Kong, Shatin, NT, Hong Kong.
authors.forename: M L
authors.initials: ML
authors.lastname: Tang
authors.forename: P M
authors.initials: PM
authors.lastname: Bentler
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D015982:Bias; D003627:Data Interpretation, Statistical; D006801:Humans; D016013:Likelihood Functions; D015233:Models, Statistical