An interesting post (and discussion) over at Andrew Gelman's (Columbia--Statistics) blog drills down on a recent paper published in The Lancet. The paper, Firearm legislation and firearm mortality in the USA: a cross-sectional, state-level study, by Bindu Kalesan et al., finds that:
"Of 25 firearm laws, nine were associated with reduced firearm mortality, nine were associated with increased firearm mortality, and seven had an inconclusive association. After adjustment for relevant covariates, the three state laws most strongly associated with reduced overall firearm mortality were universal background checks for firearm purchase (multivariable IRR 0·39 [95% CI 0·23–0·67]; p=0·001), ammunition background checks (0·18 [0·09–0·36]; p<0·0001), and identification requirement for firearms (0·16 [0·09–0·29]; p<0·0001)."
What the paper's skeptics (and critics) note include the results' strength and a healthy skepticism about laws' ability to independently account for change of such magnitude.
UPDATE: The paper's authors have quite helpfully responded publicly (here) to some of the critiques. One concern involves the stability of results flowing from a model that includes an N of 50 yet 25 predictors. As Kalesan et al. note in their response: "The critiques [partly] rest on the limitations of the sample size and on the model robustness. However, as we indicated in the paper, and in the accompanying statistical appendices, we ran an exhaustive set of sensitivity analyses and found the results robust to multiple challenges. In particular, we provide sensitivity analysis by using the change in gun death rates from 2008 to 2010 as the outcome and found results similar to the main results."