Abstract
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.
| Original language | English |
|---|---|
| Number of pages | 17 |
| Journal | Crime and Delinquency |
| Volume | Online First |
| Early online date | 22 Dec 2020 |
| DOIs | |
| Publication status | E-pub ahead of print - 22 Dec 2020 |
Keywords
- Log-linear modeling
- iImation criteria
- Modern slavery
- BIC
- AIC
Access to Document
- Cruyff_2020_CD_Humantrafficking_CC
Copyright © The Author(s) 2020. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).