NotesFAQContact Us
Search Tips
Peer reviewed Peer reviewed
Direct linkDirect link
ERIC Number: EJ883974
Record Type: Journal
Publication Date: 2010
Pages: 20
Abstractor: As Provided
Reference Count: 21
ISSN: ISSN-1076-9986
Stochastic Approximation Methods for Latent Regression Item Response Models
von Davier, Matthias; Sinharay, Sandip
Journal of Educational and Behavioral Statistics, v35 n2 p174-193 2010
This article presents an application of a stochastic approximation expectation maximization (EM) algorithm using a Metropolis-Hastings (MH) sampler to estimate the parameters of an item response latent regression model. Latent regression item response models are extensions of item response theory (IRT) to a latent variable model with covariates serving as predictors of the conditional distribution of ability. Applications to estimating latent regression models for National Assessment of Educational Progress (NAEP) data from the 2000 Grade 4 mathematics assessment and the Grade 8 reading assessment from 2002 are presented and results of the proposed method are compared to results obtained using current operational procedures. (Contains 3 tables and 4 figures.)
SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail:; Web site:
Publication Type: Journal Articles; Reports - Research
Education Level: Elementary Education; Grade 4; Grade 8; Junior High Schools; Middle Schools; Secondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Assessments and Surveys: National Assessment of Educational Progress