Log-linear multidimensional Rasch model for capture-recapture
Publication date
2014-08-19
Editors
Gilli, Manfred
Gonzalez-Rodriguez, Gil
Nieto-Reyes, Alicia
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Supervisors
DOI
Document Type
Part of book
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Abstract
The traditional capture-recapture method assumes homogeneity of the capture probabilities. However, differences of character or behaviour between individuals may occur and models that allow for varying susceptibility to capture over individuals and unequal catchability have been proposed and psychometric models, such as the Rasch model, were successfully applied. In the present work, we propose the use of the multidimensional Rasch model in the capture-recapture context. We assume that lists may be divided into two or more subgroups, such that they can be viewed as indicators of the latent variables which account for correlations among lists. We show how to express the probability of a generic capture profile in terms of log-linear multidimensional Rasch model and apply the methodology to a real data set.
Keywords
Rasch model, capture-recapture, heterogeneity, log-linear model, EM algorithm
Citation
Pelle, E, Hessen, D J & van der Heijden, P G M 2014, Log-linear multidimensional Rasch model for capture-recapture. in M Gilli, G Gonzalez-Rodriguez & A Nieto-Reyes (eds), Proceedings of COMPSTAT 2014 : 21st International Conference on Computational Statistics. Genéve, pp. 435-442.