Analysis of structural equation models with censored or truncated data via EM algorithm

被引：9

作者：

Tang, ML ^{[1
]}

Lee, SY ^{[1
]}

机构：

[1] Chinese Univ Hong Kong, Dept Stat, Shatin, NT, Hong Kong

来源：

COMPUTATIONAL STATISTICS & DATA ANALYSIS | 1998年 / 27卷 / 01期

关键词：

structural equation models; non-ignorable missing mechanism; generalized censoring mechanism (GCM); maximum-likelihood estimation; generalized EM algorithm; censored data; truncated data;

D O I：

10.1016/S0167-9473(97)80040-0

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this article, we delineate the analysis of structural equation models with censored data or truncated data with the number of unmeasured subjects under the framework of the generalized censoring mechanism (GCM), one of the most popular non-ignorable missing mechanisms. An EM algorithm for maximum-likelihood estimation in structural equation models with censored data will be presented. By reformulating the censored-data problem into non-ignorable missing-data problem, the maximization procedure is shown to be simplified. A simulated data set will be used as an illustrative example. (C) 1998 Elsevier Science B.V. All rights reserved.

引用

页码：33 / 46

页数：14

共 50 条

[31] Bayesian Analysis of Skew Gaussian Spatial Models Based on Censored Data
Tadayon, Vahid
Khaledi, Majid Jafari
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2015, 44 (09) : 2431 - 2441
[32] blavaan: Bayesian Structural Equation Models via Parameter Expansion
Merkle, Edgar C.
Rosseel, Yves
JOURNAL OF STATISTICAL SOFTWARE, 2018, 85 (04): : 1 - 30
[33] Accurate Estimation of Structural Equation Models with Remote Partitioned Data
Snoke, Joshua
Brick, Timothy
Slavkovic, Aleksandra
PRIVACY IN STATISTICAL DATABASES: UNESCO CHAIR IN DATA PRIVACY, 2016, 9867 : 190 - 209
[34] Transformation Structural Equation Models With Highly Nonnormal and Incomplete Data
Liu, Pengfei
Chen, Ji
Lu, Zhaohua
Song, Xinyuan
STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL, 2015, 22 (03) : 401 - 415
[35] Hierarchical Bayesian models for robust estimation and censored data analysis in animal breeding
Cardoso, Fernando Flores
de Magalhaes Rosa, Guilherme Jordao
Tempelman, Robert John
de Almeida Torres Junior, Roberto Augusto
REVISTA BRASILEIRA DE ZOOTECNIA-BRAZILIAN JOURNAL OF ANIMAL SCIENCE, 2009, 38 : 72 - 80
[36] EFFECT ANALYSIS AND CAUSATION IN LINEAR STRUCTURAL EQUATION MODELS
SOBEL, ME
PSYCHOMETRIKA, 1990, 55 (03) : 495 - 515
[37] Network Topology Inference via Elastic Net Structural Equation Models
Traganitis, Panagiotis A.
Shen, Yanning
Giannakis, Georgios B.
2017 25TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), 2017, : 146 - 150
[38] Theory and method for constrained estimation in structural equation models with incomplete data
Tang, ML
Bentler, PM
COMPUTATIONAL STATISTICS & DATA ANALYSIS, 1998, 27 (03) : 257 - 270
[39] Identifying Aberrant Data in Structural Equation Models With IRLS-ADF
Kim, Dale S.
Reise, Steven P.
Bentler, Peter M.
STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL, 2018, 25 (03) : 343 - 358
[40] Analysis of dependent left-truncated and right-censored competing risks data with partially observed failure causes
Wang, Liang
Tripathi, Yogesh Mani
Dey, Sanku
Zhang, Chunfang
Wu, Ke
MATHEMATICS AND COMPUTERS IN SIMULATION, 2022, 194 : 285 - 307

← 1 2 3 4 5 →