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Impact of Policy on Children
September 8, 2020

Study Designs and Statistical Methods for Studies of Child and Adolescent Health Policies

Author Affiliations
  • 1Vanderbilt University Medical Center, Nashville, Tennessee
  • 2Statistical Editor, JAMA Pediatrics
  • 3Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
JAMA Pediatr. 2020;174(10):925-927. doi:10.1001/jamapediatrics.2020.3408

Rigorous empirical studies of the effect of a policy intervention seek to consider (or estimate) what outcomes are (or would be) with the policy compared with what outcomes are (or would be) without the policy. For example, consider whether decriminalization of adult marijuana use (medical or recreational) is associated with adolescent marijuana use.1 As detailed below, one can use data over time from states that did and did not decriminalize adult marijuana use and compare observed trends in adolescent marijuana use among states with the policy change to expected (or predicted) trends in marijuana use, had the policy change not occurred, to estimate the policy effect. Of note, the policy effect could also be estimated in settings in which there is not a comparison group, such as if marijuana were decriminalized nationwide. We focus on settings often referred to as group panel data, for which there are aggregate data available on groups of interest with outcomes measured over time both before and after the policy change and ideally with comparison groups that did not experience a policy change; individual-level data could also be available within the groups. The data in some cases correspond with full population data at each time point; in others, there might be repeated cross-sections of data, such as annual surveys of marijuana use among 10th graders. As long as the data can be thought of as representative of the unit under study, either data structure can be appropriate. We broadly consider the selection of data to examine (eg, the units to study, the time period to examine) as well as the statistical methods that can be used to estimate policy effects using that data.

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