NotesFAQContact Us
Collection
Advanced
Search Tips
Peer reviewed Peer reviewed
PDF on ERIC Download full text
ERIC Number: EJ1110899
Record Type: Journal
Publication Date: 2004-May
Pages: 69
Abstractor: As Provided
Reference Count: 29
ISBN: N/A
ISSN: EISSN-2330-8516
Joint and Conditional Maximum Likelihood Estimation for the Rasch Model for Binary Responses. Research Report. RR-04-20
Haberman, Shelby J.
ETS Research Report Series, May 2004
The usefulness of joint and conditional maximum-likelihood is considered for the Rasch model under realistic testing conditions in which the number of examinees is very large and the number is items is relatively large. Conditions for consistency and asymptotic normality are explored, effects of model error are investigated, measures of prediction are estimated, and generalized residuals are developed.
Educational Testing Service. Rosedale Road, MS19-R Princeton, NJ 08541. Tel: 609-921-9000; Fax: 609-734-5410; e-mail: RDweb@ets.org; Web site: https://www.ets.org/research/policy_research_reports/ets
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A