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Table 2 Performance of RTM using hit rate as the forecasting performance measure

From: Systematic review and meta-analysis of risk terrain modelling (RTM) as a spatial forecasting method

Study Crime type Hit rate (high-very high risk cells)
Valasik et al., (2019) Lethal violence 23%
Kocher and Leitner (2015) Burglary 25%
Kocher and Leitner (2015) Auto theft 25.7%
Giménez-Santana et al., (2018a, 2018b) Assault 29%
Giménez-Santana et al., (2018a, 2018b) Homicide 32%
Valasik (2018) Gang violence 33%
Dugato et al., (2018) Burglary 35.7%
Kocher and Leitner (2015) Assault (spring) 37%
Anyinam (2015) Robbery 39%
Giménez-Santana et al., (2018a, 2018b) Theft 40%
Ohyama and Amemiya (2018) Thefts from vehicles 40.9%
Anyinam (2015) Non-fatal shootings 41%
Giménez-Santana et al., (2018a, 2018b) Alcohol related traffic crashes 41%
Caplan (2011) Shootings 42%
Dugato (2013) Robbery 43%
Onat and Gul (2018) Terrorist acts 43%
Kocher and Leitner (2015) Robbery 43.5%
Kocher and Leitner (2015) Assault (summer) 44.4%
Caplan et al., (2013a, 2013b) Violent crime 45%
Drawve et al., (2016) Gun crime 48%
Marchment et al., (2019) Bombings 50%
Marchment et al., (2019) Bomb hoaxes 50%
Daley et al., (2016) Child maltreatment 52%
Anyinam (2015) Homicide 57%
Escuerdo & Ramírez (2018) Illicit drug markets 64%
Dugato et al., (2017) Mafia homicide 85%
Onat et al., (2018) Drug crime 85%