Stata/SQL/Python integration to emulate prospective cohort studies from big register data

Matteo Marrazzo and Nicola Orsini
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Matteo Marrazzo: Karolinska Institutet

Nordic and Baltic Stata Users' Group Meeting 2019 from Stata Users Group

Abstract: The possibilities of using Stata to interrogate and analyze big data are not widely known among health researchers. However, the ability to meld different programming tools is becoming gradually more important with the increasing mainstream availability of big data sources. The aim of this presentation is to illustrate, using existing commands such as odbc and python, how to emulate and analyze large prospective cohorts from a collection of big national registers, harvesting the power of the different engines available (for example, SQL to handle relational databases and the preprocess phase, Stata to easily perform advanced statistical analyses and Python to implement well-known modules and packages for data manipulation and plots). I use a case study in pharmaco-epidemiology to illustrate the potential of using Stata to both design and analyze such complex and large datasets.

Date: 2020-08-20
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http://fmwww.bc.edu/repec/ncon19/nordic19_marrazzo.pdf

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Persistent link: https://EconPapers.repec.org/RePEc:boc:ncon19:12

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