Upgrading Seat Belt Laws to Primary Enforcement: Semi-Bayesian Analysis

Background: Background sentence.

Methods: We did this. And this.

Results: We found this.

Conclusions: What it all means.

Introduction

A number of states may be considering passing legislation to upgrade their mandatory seat belt laws from secondary to primary enforcement. The map below shows the current distribution of levels of mandatory seat belt law enforcement.  

For example, the CDC's Motor Vehicle Prioritizing Interventions and Cost Calculator for States (MV PICCS) presently uses estimates for the effectiveness of upgrading seat belt laws to primary enforcement based on the .

On the other hand, one might argue that states that presently have not upgraded to 
  • Take a Bayesian approach to prior evidence on the impact of upgrading to primary enforcement on motor vehicle accidents.
    • Similar for seat belt use as outcome?
  • Use data augmentation approach for semi-Bayesian approach.
  • Compare with MCMC approach without adjustments for clustering by state (not feasible yet in Bayesian framework?)
In particular, it seems odd to adopt a purely frequentist stance when considering the question of whether states with existing laws maintaining secondary enforcement should upgrade their laws to primary enforcement. In this papers, we are chiefly concerned with providing an estimate of the impact of upgrading to primary enforcement on occupant fatalities, rather than an all-things-considered judgement. Clearly, concerns about paternalism, police harassment, and the additional costs of enforcement (such as "Click-It-Or-Ticket" or other media campaigns) are relevant to any policy decision, but we put those questions to the side for the present paper.
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Improvements in computing power and the incorporation of Bayesian analytic techniques in commercial and open source software has greatly improved the prospects for utilizing Bayesian analysis in policy research