<p>(a) County-by-county posterior estimates of the risk ratio of being {black, armed, and shot by police} to being {white, armed, and shot by police}. Grey bars are county-specific 95% PCI estimates. The blue bar is the nation-wide pooled 95% PCI estimate. The points on the error bars are posterior medians. Data are plotted on the log scale, but are labeled on the natural scale. (b) Map of county-specific posterior median estimates of the risk ratio of being {black, armed, and shot by police} to being {white, armed, and shot by police}.</p
Black denotes regions with strictly negative credible intervals, white denotes regions with strictly...
<p>Predicted rates per 100,000 individuals. Red, orange, and yellow colors indicate areas with highe...
<p>Circles show posterior medians, thick bars show inter-quartile ranges of the posteriors, and thin...
<p>(a) County-by-county posterior estimates of the risk ratio of being {black, unarmed, and shot by ...
<p>(a) County-by-county posterior estimates of the risk ratio of being {black, armed, and shot by po...
<p>(a) County-by-county posterior estimates of the risk ratio of being {black, unarmed, and shot by ...
<p>(a) County-by-county posterior estimates of the risk ratio of being {white, armed, and shot by po...
<p>(a) County-by-county posterior estimates of the risk ratio of being {hispanic, unarmed, and shot ...
<p>(a) County-by-county posterior estimates of the risk ratio of being {hispanic, armed, and shot by...
<p>Values are: posterior mean (posterior standard deviation) of the regression coefficients. The sym...
(A) Map of census sector level spatial incidence risk pattern exp(ξi). (B) Posterior probability dis...
A geographically-resolved, multi-level Bayesian model is used to analyze the data presented in the U...
<p>Posterior median of county–specific differential trends. Counties with values closer to 0 indicat...
A geographically-resolved, multi-level Bayesian model is used to analyze the data pre-sented in the ...
<p>Maps of 95% (A) and 80% (B) posterior probabilities for the unadjusted total spatial effects.</p
Black denotes regions with strictly negative credible intervals, white denotes regions with strictly...
<p>Predicted rates per 100,000 individuals. Red, orange, and yellow colors indicate areas with highe...
<p>Circles show posterior medians, thick bars show inter-quartile ranges of the posteriors, and thin...
<p>(a) County-by-county posterior estimates of the risk ratio of being {black, unarmed, and shot by ...
<p>(a) County-by-county posterior estimates of the risk ratio of being {black, armed, and shot by po...
<p>(a) County-by-county posterior estimates of the risk ratio of being {black, unarmed, and shot by ...
<p>(a) County-by-county posterior estimates of the risk ratio of being {white, armed, and shot by po...
<p>(a) County-by-county posterior estimates of the risk ratio of being {hispanic, unarmed, and shot ...
<p>(a) County-by-county posterior estimates of the risk ratio of being {hispanic, armed, and shot by...
<p>Values are: posterior mean (posterior standard deviation) of the regression coefficients. The sym...
(A) Map of census sector level spatial incidence risk pattern exp(ξi). (B) Posterior probability dis...
A geographically-resolved, multi-level Bayesian model is used to analyze the data presented in the U...
<p>Posterior median of county–specific differential trends. Counties with values closer to 0 indicat...
A geographically-resolved, multi-level Bayesian model is used to analyze the data pre-sented in the ...
<p>Maps of 95% (A) and 80% (B) posterior probabilities for the unadjusted total spatial effects.</p
Black denotes regions with strictly negative credible intervals, white denotes regions with strictly...
<p>Predicted rates per 100,000 individuals. Red, orange, and yellow colors indicate areas with highe...
<p>Circles show posterior medians, thick bars show inter-quartile ranges of the posteriors, and thin...