How Neighborhood Characteristics Influence Neighborhood Crimes: A Bayesian Hierarchical Spatial Analysis
Abstract
:1. Introduction
2. Materials and Methods
2.1. Paterson, New Jersey
2.2. Violent Crimes, Harmful Products, Urban Prosperity, and Ethnic Landscape
2.3. Bayesian Hierarchical Modeling Approach
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Variables | Mean | sd | 0.025 Quant | 0.5 Quant | 0.975 Quant |
---|---|---|---|---|---|
(Intercept) | 0.602 | 0.435 | −0.255 | 0.604 | 1.453 |
Pop | 0.220 | 0.098 | 0.030 | 0.218 | 0.416 |
MHI | −0.021 | 0.004 | −0.028 | −0.021 | −0.014 |
pcthisp | 1.590 | 0.480 | 0.649 | 1.589 | 2.534 |
pctaa | 1.995 | 0.415 | 1.183 | 1.994 | 2.813 |
alc | 0.052 | 0.037 | −0.020 | 0.052 | 0.125 |
tbc | 0.103 | 0.021 | 0.062 | 0.103 | 0.144 |
abdp | 0.005 | 0.002 | 0.000 | 0.005 | 0.010 |
Variables | Mean | sd | 0.025 Quant | 0.5 Quant | 0.975 Quant |
---|---|---|---|---|---|
(Intercept) | 0.584 | 0.447 | −0.301 | 0.586 | 1.457 |
Pop | 0.219 | 0.098 | 0.031 | 0.218 | 0.414 |
MHI | −0.021 | 0.004 | −0.028 | −0.021 | −0.014 |
pcthisp | 1.602 | 0.493 | 0.635 | 1.601 | 2.574 |
pctaa | 2.018 | 0.438 | 1.163 | 2.016 | 2.886 |
alc | 0.053 | 0.037 | −0.020 | 0.053 | 0.126 |
tbc | 0.101 | 0.021 | 0.061 | 0.101 | 0.143 |
abdp | 0.005 | 0.002 | 0.000 | 0.005 | 0.010 |
Variable | N | Mean | Std. Dev. | Min | Pctl. 25 | Pctl. 75 | Max |
---|---|---|---|---|---|---|---|
Pop.b * | 105 | 0.256 | 0.023 | 0.198 | 0.244 | 0.274 | 0.293 |
Pop.t ** | 105 | 1.912 | 0.252 | 1.243 | 1.793 | 2.09 | 2.324 |
MHI.b | 105 | −0.019 | 0.004 | −0.033 | −0.021 | −0.017 | −0.01 |
MHI.t | 105 | −2.427 | 0.446 | −3.331 | −2.776 | −2.123 | −1.28 |
pcthisp.b | 105 | 1.121 | 0.02 | 1.081 | 1.104 | 1.136 | 1.161 |
pcthisp.t | 105 | 1.601 | 0.029 | 1.527 | 1.585 | 1.625 | 1.652 |
pctaa.b | 105 | 1.531 | 0.014 | 1.498 | 1.519 | 1.542 | 1.552 |
pctaa.t | 105 | 2.252 | 0.029 | 2.187 | 2.231 | 2.271 | 2.317 |
tbc.b | 105 | 0.083 | 0.009 | 0.059 | 0.078 | 0.09 | 0.105 |
tbc.t | 105 | 1.973 | 0.405 | 1.048 | 1.68 | 2.214 | 2.993 |
alc.b | 105 | 0.066 | 0.014 | 0.029 | 0.057 | 0.076 | 0.107 |
alc.t | 105 | 1.079 | 0.248 | 0.359 | 0.916 | 1.235 | 1.649 |
abdp.b | 105 | 0.007 | 0.001 | 0.004 | 0.006 | 0.007 | 0.008 |
abdp.t | 105 | 1.129 | 0.24 | 0.643 | 0.969 | 1.242 | 2.045 |
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Yu, D.; Fang, C. How Neighborhood Characteristics Influence Neighborhood Crimes: A Bayesian Hierarchical Spatial Analysis. Int. J. Environ. Res. Public Health 2022, 19, 11416. https://doi.org/10.3390/ijerph191811416
Yu D, Fang C. How Neighborhood Characteristics Influence Neighborhood Crimes: A Bayesian Hierarchical Spatial Analysis. International Journal of Environmental Research and Public Health. 2022; 19(18):11416. https://doi.org/10.3390/ijerph191811416
Chicago/Turabian StyleYu, Danlin, and Chuanglin Fang. 2022. "How Neighborhood Characteristics Influence Neighborhood Crimes: A Bayesian Hierarchical Spatial Analysis" International Journal of Environmental Research and Public Health 19, no. 18: 11416. https://doi.org/10.3390/ijerph191811416