Multiple System Estimation of Victims of Human Trafficking: Model Assessment and Selection | Zendy

Maarten Cruyff | Zendy; Antony M. Overstall | Zendy; Michail Papathomas | Zendy; Rachel S. McCrea | Zendy

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Multiple System Estimation of Victims of Human Trafficking: Model Assessment and Selection

Author(s) -

Maarten Cruyff,

Antony M. Overstall,

Michail Papathomas,

Rachel S. McCrea

Publication year - 2020

Publication title -

crime and delinquency

Language(s) - English

Resource type - Journals

eISSN - 1552-387X

pISSN - 0011-1287

DOI - 10.1177/0011128720981908

Subject(s) - contingency table , estimation , covariate , selection (genetic algorithm) , table (database) , model selection , population , computer science , poison control , human trafficking , log linear model , statistics , econometrics , data mining , linear model , machine learning , mathematics , engineering , medicine , psychology , criminology , medical emergency , environmental health , systems engineering

Recently, multiple systems estimation (MSE) has been applied to estimate the number of victims of human trafficking in different countries. The estimation procedure consists of a log-linear analysis of a contingency table of population registers and covariates. As the number of potential models increases exponentially with the number of registers and covariates, it is practically impossible to fit and compare all models. Therefore, the model search needs to be restricted to a small subset of all potential models. This paper addresses principles and criteria for model assessment and selection for MSE of human trafficking with special attention to sparsity which is typical to human trafficking data. The concepts are illustrated on data from Slovakia and Romania.

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