Predicting criminal recidivism using registration data

DOI

These data are from two papers that research the predictability of general, violent and sexual recidivism using registration data. It consists of 2005/2006 conviction cohorts and includes both binary and survival outcome variants. The subsamples for training and testing sets are included so the data is independent of random number generation implementations.

Date: 2018-02-27

Identifier
DOI https://doi.org/10.17026/dans-23p-7uuu
Metadata Access https://phys-techsciences.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/dans-23p-7uuu
Provenance
Creator N Tollenaar
Publisher DANS Data Station Phys-Tech Sciences
Contributor SIBA WODC
Publication Year 2018
Rights DANS Licence; info:eu-repo/semantics/closedAccess; https://doi.org/10.17026/fp39-0x58
OpenAccess false
Contact SIBA WODC (Ministerie van Justitie)
Representation
Resource Type Dataset
Format application/pdf; application/x-stata-14; application/x-spss-por; application/x-spss-sav; application/x-stata; application/zip
Size 219840; 193756; 1768722; 1332662; 899686; 4665384; 1762306; 567958; 323063; 136692; 84654; 4805384; 2112974; 1281142; 4505222; 2143560; 1305022; 60336; 22184
Version 2.0
Discipline Other