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- Title
Bootstrapping the estimated latent distribution of the two-parameter latent trait model.
- Authors
Knott, M.; Tzamourani, P.
- Abstract
This paper focuses on the two-parameter latent trait model for binary data. Although the prior distribution of the latent variable is usually assumed to be a standard normal distribution, that prior distribution can be estimated from the data as a discrete distribution using a combination of EM algorithms and other optimization methods. We assess with what precision we can estimate the prior from the data, using simulations and bootstrapping. A novel calibration method is given to check that near optimality is achieved for the bootstrap estimates. We find that there is sufficient information on the prior distribution to be informative, and that the bootstrap method is reliable. We illustrate the bootstrap method for two sets of real data.
- Subjects
STATISTICAL bootstrapping; VARIABILITY (Psychometrics); LATENT structure analysis; PSYCHOMETRICS; LATENT variables; MULTIVARIATE analysis
- Publication
British Journal of Mathematical & Statistical Psychology, 2007, Vol 60, Issue 1, p175
- ISSN
0007-1102
- Publication type
Article
- DOI
10.1348/000711006X107539