Estimation and Hypothesis Testing in Linear Models Containing Measurement Error

J. Scott Long
Additional contact information
J. Scott Long: Cornell University

Sociological Methods & Research, 1976, vol. 5, issue 2, 157-206

Abstract: This paper reviews Joreskog's model for the analysis of covariance structures by first introducing the simpler case of confirmatory factor analysis. The mathematical results necessary for estimation and hypothesis testing are presented in a way which should be more accessible to sociologists than the original sources. The usefulness of Joreskog's techniques is indicated by reformulating a series of models which have been estimated by sociologists using techniques without statistical justification in the format of covariance structures. Identification is considered in this context. The argument is made that these methods can greatly extend our ability to construct structural equation models containing measurement error.

Date: 1976
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/004912417600500202 (text/html)

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:sae:somere:v:5:y:1976:i:2:p:157-206

DOI: 10.1177/004912417600500202

Access Statistics for this article

More articles in Sociological Methods & Research
Bibliographic data for series maintained by SAGE Publications ().