Table 1. Logistic regression models predicting the mortality of police shootings in the pooled sample.
| Model 1 | Model 2 | |||||
|---|---|---|---|---|---|---|
| b | SE | dy/dx (95% CI) | b | SE | dy/dx (95% CI) | |
| Black victim a | -.490*** | .099 | -.121 (-.169, -.074) | -.277* | .108 | -.069 (-.121, -.016) |
| Hispanic victim a | -.133 | .086 | -.032 (-.074, .009) | .040 | .106 | .010 (-.041, .060) |
| Other victim a | .189 | .235 | .044 (-.062, .151) | .282 | .241 | .067 (-.042, .177) |
| Male victim | — | — | — | .080 | .158 | .020 (-.057, .097) |
| Age 26–35 b | — | — | — | .343*** | .087 | .085 (.043, .128) |
| Age 36–45 b | — | — | — | .531*** | .109 | .131 (.079, .183) |
| Age 46+ b | — | — | — | .665*** | .149 | .163 (.094, .232) |
| Weapon | — | — | — | .649*** | .105 | .161 (.110, .211) |
| Trauma care | — | — | — | -.018 | .110 | -.005 (-.058, .049) |
| Metro county | — | — | — | -.160 | .193 | -.039 (-.130, .052) |
| Colorado c | — | — | — | .126 | .179 | .030 (-.054, .115) |
| Texas c | — | — | — | -.199 | .118 | -.049 (-.106, .008) |
| California c | — | — | — | -.095 | .105 | -.023 (-.074, .027) |
| Intercept | .396*** | .062 | — | -.454 | .237 | — |
| N | 2,940 | 2,892 | ||||
| Wald χ2 | 32.41*** | 117.25*** | ||||
Abbreviations: SE = Robust Standard Errors clustered on 246 counties; dy/dx = Average marginal effects showing the discrete change in the outcome (fatality) when moving from the reference category (estimated using margins command in Stata v15).
Reference categories are
a White victim,
b Age 25 and under, and
c Florida, respectively.
* p < .05,
** p < .01,
*** p < .001.