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 |
|---|---|
| Pages (from-to) | 2237-2253 |
| Number of pages | 17 |
| Journal | Crime and Delinquency |
| Volume | 67 |
| Issue number | 13-14 |
| Early online date | Dec 2020 |
| DOIs | |
| Publication status | Published - Dec 2021 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 5 Gender Equality
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SDG 8 Decent Work and Economic Growth
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SDG 16 Peace, Justice and Strong Institutions
Keywords
- Aic
- Bic
- Information criteria
- Log-linear modeling
- Modern slavery
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