Log-linear multidimensional Rasch model for capture-recapture

Publication date

2014-08-19

Authors

Pelle, E.
Hessen, DavidISNI 0000000390190540
van der Heijden, PeterISNI 0000000067738801

Editors

Gilli, Manfred
Gonzalez-Rodriguez, Gil
Nieto-Reyes, Alicia

Advisors

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.