In this study, researchers assess whether latent class analysis (LCA) is a useful for classifying states based on the restrictiveness of firearm transfer laws.
Results of this study suggest that latent class analysis (LCA) is a useful technique for classifying states based on the restrictiveness of firearm transfer laws. This classification may be useful in intervention and prevention planning. The aim of the present study was to determine whether LCA could obtain a measure of the aggregate firearm transfer law environment. LCA, analysis of variance, and multinomial logistic regression were used to analyze state-level firearm transfer laws. Results indicated that a three-class solution fit the data better than a two- or four-class solution. These classes were associated with the two covariates in patterns consistent with hypotheses. (Published Abstract Provided)
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