Peer reviewedERIC Number: EJ564705
Record Type: Journal
Publication Date: 1997
Pages: N/A
Abstractor: N/A
ISBN: N/A
ISSN: ISSN-1076-9986
EISSN: N/A
Generating Multiple Imputations for Matrix Sampling Data Analyzed with Item Response Models.
Thomas, Neal; Gan, Nianci
Journal of Educational and Behavioral Statistics, v22 n4 p425-45 Win 1997
Describes and assesses missing data methods currently used to analyze data from matrix sampling designs implemented by the National Assessment of Educational Progress. Several improved methods are developed, and these models are evaluated using an EM algorithm to obtain maximum likelihood estimates followed by multiple imputation of complete data sets. (SLD)
Descriptors: Data Analysis, Item Response Theory, Matrices, Maximum Likelihood Statistics, Models, Research Design, Sampling
Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Assessments and Surveys: National Assessment of Educational Progress
Grant or Contract Numbers: N/A
