Maximum likelihood and generalized least squares analyses of two-level structural equation models

Wai-Yin Poon and Sik-Yum Lee

Statistics & Probability Letters, 1992, vol. 14, issue 1, 25-30

Abstract: A two-level structural equation model with small level-one samples and unbalanced designs is treated. Under the assumption of normality, the maximum likelihood and generalized least squares methods are employed to analyze the model. Asymptotic properties of the estimators are discussed. Results of a Monte Carlo study investigating the performance of the estimators are reported.

Keywords: Two-level; structural; equation; models; unbalanced; designs; maximum; likelihood; generalized; least; squares (search for similar items in EconPapers)
Date: 1992
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0167-7152(92)90206-K
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:14:y:1992:i:1:p:25-30

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().