Case-Deletion Diagnostics for Factor Analysis Models With Continuous and Ordinal Categorical Data

Sik-Yum Lee and Liang Xu

Sociological Methods & Research, 2003, vol. 31, issue 3, 389-419

Abstract: This article proposes a method to detect influential observations in a factor analysis model with continuous and ordinal categorical variables. The key ideas are to treat the latent factors as hypothetical missing data and then develop the diagnostic measures on the basis of the conditional expectation of the complete-data log-likelihood function in the EM algorithm. A one-step approximation is proposed to reduce the computational burden. Building blocks for achieving the diagnostic measures are computed via observations generated by the Gibbs sampler. Results from a simulation study and an illustrative real example are presented.

Date: 2003
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0049124102239081 (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:31:y:2003:i:3:p:389-419

DOI: 10.1177/0049124102239081

Access Statistics for this article

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