Logistic-regression analysis

Adjusted fatal-crash associations in 404,508 Brazilian records.

A multivariable logistic regression on Brazilian crash records compared fatal-crash odds across reported causes while controlling for time of day, road delineation, and weather. The published artifacts expose the candidate models, selected specification, coefficient result, input checksum, and runtime environment.

Raw records
463,152
404,508 modeling rows after documented exclusion
Adjusted odds ratio
11.52×
95% Wald CI 10.23–12.98
Change after adjustment
−4.9%
from 12.12× unadjusted to 11.52× adjusted

Model decision

SpecificationControls added to crash causeAICDecision
Model 5Time of day, road delineation, weather177,765.3Selected: minimum AIC
Model 4Time of day, road delineation177,917.6Not selected
Model 3Time of day, weather178,988.3Not selected
Interpretation

Adjusted association, not a causal effect.

The reported 11.52× compares crashes attributed to pedestrians walking in the road with alcohol-related crashes, conditional on the selected covariates. It does not mean pedestrian behavior causes fatality odds to increase by that amount. The interval is model-based and assumes independent records and a correctly specified logistic model.

Methods and artifacts

Data provenance

The source file is not republished. The reproduction script records its MD5 checksum (8b2672d2451e806cd7a71231ecad4cd7) so the exact input can be checked. The model excludes 58,644 rows whose road delineation was recorded as “Not Reported”; that exclusion and the resulting 404,508-row cohort are visible in the result artifact.