dc.contributor.author | Tikka, Santtu | |
dc.contributor.author | Hakanen, Jussi | |
dc.contributor.author | Saarela, Mirka | |
dc.contributor.author | Karvanen, Juha | |
dc.date.accessioned | 2022-03-24T11:14:48Z | |
dc.date.available | 2022-03-24T11:14:48Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | Tikka, S., Hakanen, J., Saarela, M., & Karvanen, J. (2021). Sima – an Open-source Simulation Framework for Realistic Large-scale Individual-level Data Generation. <i>International Journal of Microsimulation</i>, <i>14</i>(3), 27-53. <a href="https://doi.org/10.34196/IJM.00240" target="_blank">https://doi.org/10.34196/IJM.00240</a> | |
dc.identifier.other | CONVID_117395624 | |
dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/80356 | |
dc.description.abstract | We propose a framework for realistic data generation and the simulation of complex systems and demonstrate its capabilities in a health domain example. The main use cases of the framework are predicting the development of variables of interest, evaluating the impact of interventions and policy decisions, and supporting statistical method development. We present the fundamentals of the framework by using rigorous mathematical definitions. The framework supports calibration to a real population as well as various manipulations and data collection processes. The freely available open-source implementation in R embraces efficient data structures, parallel computing, and fast random number generation, hence ensuring reproducibility and scalability. With the framework, it is possible to run daily-level simulations for populations of millions of individuals for decades of simulated time. An example using the occurrence of stroke, type 2 diabetes, and mortality illustrates the usage of the framework in the Finnish context. In the example, we demonstrate the data collection functionality by studying the impact of nonparticipation on the estimated risk models and interventions related to controlling excessive salt consumption. | en |
dc.format.mimetype | application/pdf | |
dc.language.iso | eng | |
dc.publisher | International Microsimulation Association | |
dc.relation.ispartofseries | International Journal of Microsimulation | |
dc.rights | CC BY 4.0 | |
dc.title | Sima – an Open-source Simulation Framework for Realistic Large-scale Individual-level Data Generation | |
dc.type | article | |
dc.identifier.urn | URN:NBN:fi:jyu-202203242043 | |
dc.contributor.laitos | Matematiikan ja tilastotieteen laitos | fi |
dc.contributor.laitos | Informaatioteknologian tiedekunta | fi |
dc.contributor.laitos | Department of Mathematics and Statistics | en |
dc.contributor.laitos | Faculty of Information Technology | en |
dc.contributor.oppiaine | Human and Machine based Intelligence in Learning | fi |
dc.contributor.oppiaine | Tietotekniikka | fi |
dc.contributor.oppiaine | Koulutusteknologia ja kognitiotiede | fi |
dc.contributor.oppiaine | Tilastotiede | fi |
dc.contributor.oppiaine | Multiobjective Optimization Group | fi |
dc.contributor.oppiaine | Laskennallinen tiede | fi |
dc.contributor.oppiaine | Resurssiviisausyhteisö | fi |
dc.contributor.oppiaine | Human and Machine based Intelligence in Learning | en |
dc.contributor.oppiaine | Mathematical Information Technology | en |
dc.contributor.oppiaine | Learning and Cognitive Sciences | en |
dc.contributor.oppiaine | Statistics | en |
dc.contributor.oppiaine | Multiobjective Optimization Group | en |
dc.contributor.oppiaine | Computational Science | en |
dc.contributor.oppiaine | School of Resource Wisdom | en |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | |
dc.type.coar | http://purl.org/coar/resource_type/c_2df8fbb1 | |
dc.description.reviewstatus | peerReviewed | |
dc.format.pagerange | 27-53 | |
dc.relation.issn | 1747-5864 | |
dc.relation.numberinseries | 3 | |
dc.relation.volume | 14 | |
dc.type.version | publishedVersion | |
dc.rights.copyright | © 2021, Tikka et al. | |
dc.rights.accesslevel | openAccess | fi |
dc.relation.grantnumber | 311877 | |
dc.subject.yso | terveysala | |
dc.subject.yso | tietojärjestelmät | |
dc.subject.yso | ennusteet | |
dc.subject.yso | avoin lähdekoodi | |
dc.subject.yso | matemaattiset mallit | |
dc.subject.yso | tietojenkäsittely | |
dc.subject.yso | tietorakenteet | |
dc.subject.yso | lähdekoodit | |
dc.subject.yso | tilastomenetelmät | |
dc.subject.yso | simulointi | |
dc.format.content | fulltext | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p26126 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p3927 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p3297 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p17089 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p11401 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p2407 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p25964 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p9343 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p3127 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p4787 | |
dc.rights.url | https://creativecommons.org/licenses/by/4.0/ | |
dc.relation.doi | 10.34196/IJM.00240 | |
dc.relation.funder | Research Council of Finland | en |
dc.relation.funder | Suomen Akatemia | fi |
jyx.fundingprogram | Research profiles, AoF | en |
jyx.fundingprogram | Profilointi, SA | fi |
jyx.fundinginformation | This work belongs to the thematic research area “Decision analytics utilizing causal models and multiobjective optimization” (DEMO) supported by Academy of Finland (grant number 311877). | |
dc.type.okm | A1 | |