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Table 3 Results of negative binomial regression analysis for larcenies

From: A Spatio-temporal Analysis of Crime at Washington, DC Metro Rail: Stations’ Crime-generating and Crime-attracting Characteristics as Transportation Nodes and Places

 

Larceny

 

Peak

Non-peak day

Non-peak night

Incident Rate Ratios of Node Variables

Connectedness (crime generator)

7.026**

4.020

2.928

Remoteness (crime attractor)

2.321†

0.981

6.688

Incident Rate Ratios of Place Variables

Accessibility and Activity Level (crime generator):

   

AAL_Peak

0.736

--

--

AAL_Non-peak day

--

0.965

--

AAL_non-peak night

--

--

2.782†

SES (crime attractor)

1.726**

1.651*

1.192

Other Crimes (crime attractor):

   

Robbery

0.968

0.962

0.760

R2 = 0.06

R2 = 0.04

R2 = 0.06

  1. *Significant at 0.05 p-level
  2. **Significant at 0.01 p-level
  3. †Significant at 0.1 p-level