Literary Cafe series: Policy analysis (Part 2) - Interrupted Times Series Analysis with publicly available data

I’m back with some Literary Cafe series updates.

I have regularly informal discussions with my students about interesting papers in the biomedical sciences. Recently, we discussed a great paper by Jurecka and colleagues on the impact of a state-wide law to change the definition of fentanyl possession on opioid-related overdose death rates.

Jurecka and colleagues used publicly available data to perform their research, and I wanted to show my students how this was done using CDC WONDER data. Hence, I started this Literary Care series to document these exercises for others to learn from.

Last month, I wrote an article on how to get data from the CDC WONDER site, which you can read here. I considered this Part 1 (Getting the data).

This is the second part of a two-part series that illustrates how to use publicly available data to replicate the findings from a published study. In Part 2, I use the data from Part 1 to analyze the impact of the statwide fentanyl possession law on opioid-related overdose death rates using an interrupted time series analysis. I posted this on my RPubs site (link) along with part 1 (link).

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Literary Cafe series - Getting Data From CDC WONDER

This is Part 1 on a series of articles that I plan to write on how to perform analyses using publicly available data inspired by published studies.

Hence, I wrote an article on how to get death data from CDC WONDER, which I posted on my RPubs site here.

I’m not sure how these articles will evolve, so I’ll start with something simple like this first part, which is to gather the data to perform the analysis (Part 2 is available here).

Meanwhile, I think I’ll call these series of articles, “Literary Cafe series.” (Note: I know that this title needs work.)

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