A Public Health Law Research Program “Methods Guide,” created by a leading public health law researcher from the PHLR Methods Core group, is designed to help public health professionals understand how to conduct research in law, and help legal professionals understand scientific methods. Methods Guides are organized by their applicability to the stages of a project, from the development of the research questions and design of the study, through the selection of measures and collection of data, to analysis and dissemination.
A Public Health Law Research Program “legal dataset” is a collection of systematically gathered data that reflect the features of a specific body of laws. Datasets are created by employing scientifically valid methods for measuring law. All laws in each dataset are coded to allow for quantitative analysis. The coding scheme is provided in a codebook. The process for collecting the data is provided in a research protocol. For additional information, please refer to our white paper on measuring law and our webinar on creating a public health law dataset. Legal datasets created under the auspices of our program will be made publicly available the Inter-university Consortium for Political and Social Research, and selected datasets will be posted here.
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The Public Health Law Research program is dedicated to building the evidence base for public health law. In pursuing this aim, we fund and conduct a diverse array of research activities ranging from formative efforts that identify important research questions to the generation of legal data sets to experiments employing various methodological designs.
As a service to policy-makers and other consumers of NPO research, we have organized our resources according to this hierarchy of evidence, which depicts levels of the scientific authority.
In general, resources higher up the pyramid are less susceptible to bias and therefore provide more robust evidence about the effects of public health laws. Experimental designs, for example, utilize randomization and double-blinding to reduce selection and measurement biases making them more powerful tools for understanding causal relationships than quasi-experimental and observational designs. At the top of our pyramid are studies that use systematic processes such as meta-analysis to assess a question in light of a body of primary studies that have examined it. At the bottom of our pyramid are foundational resources like legal datasets and papers setting out research agendas. The bulk of our resources are primary studies in the middle two levels.
While this hierarchy reflects judgments about the authority of various designs, it does not suggest that research employing a design from a higher level is always more scientifically authoritative than research conducted in a design from a lower level.