title: A log-linear multidimensional Rasch model for capture-recapture.
abstract: In this paper, a log-linear multidimensional Rasch model is proposed for capture-recapture analysis of registration data. In the model, heterogeneity of capture probabilities is taken into account, and registrations are viewed as dichotomously scored indicators of one or more latent variables that can account for correlations among registrations. It is shown how the probability of a generic capture profile is expressed under the log-linear multidimensional Rasch model and how the parameters of the traditional log-linear model are derived from those of the log-linear multidimensional Rasch model. Finally, an application of the model to neural tube defects data is presented.
authors.affiliation: Department of Economics, Statistics and Finance, University of Calabria, Arcavacata di Rende, CS, Italy.
authors.forename: E
authors.initials: E
authors.lastname: Pelle
authors.affiliation: Department of Methodology and Statistics, Utrecht University, Utrecht, The Netherlands.
authors.forename: D J
authors.initials: DJ
authors.lastname: Hessen
authors.affiliation: Department of Methodology and Statistics, Utrecht University, Utrecht, The Netherlands.|S3RI, University of Southampton, Southampton, U.K.
authors.forename: P G M
authors.initials: PG
authors.lastname: van der Heijden
mesh_terms: D000465:Algorithms; D004812:Epidemiologic Methods; D006801:Humans; D007231:Infant, Newborn; D015233:Models, Statistical; D009426:Netherlands / Q000453:epidemiology; D009436:Neural Tube Defects / Q000453:epidemiology*; D011159:Population Surveillance; D011336:Probability
keywords: EM algorithm; Rasch model; capture-recapture; heterogeneity; log-linear model; measurement invariance