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    Home»Artificial Intelligence»Harmonizing and Pooling Datasets for Health Research in R | by Rodrigo M Carrillo Larco, MD, PhD | Jan, 2025
    Artificial Intelligence

    Harmonizing and Pooling Datasets for Health Research in R | by Rodrigo M Carrillo Larco, MD, PhD | Jan, 2025

    Team_AIBS NewsBy Team_AIBS NewsJanuary 22, 2025No Comments1 Min Read
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    R code to extract knowledge from distinctive datasets and mix them in a single harmonized dataset prepared for seamless evaluation

    Towards Data Science

    Photograph by Claudio Schwarz on Unsplash

    My tutorial analysis overwhelmingly contains figuring out datasets for well being analysis, harmonizing them, and mixing (pooling) the person datasets to research them collectively. This implies combining datasets throughout populations, research websites, or nations. It additionally means combining variables in order that they are often successfully analyzed collectively. In different phrases, I work within the knowledge pooling area the place I’ve been full time since 2017.

    I’ll define the methodology I observe to extract knowledge from particular person datasets, and to mix the person datasets into one pooled dataset prepared for evaluation. That is primarily based on over seven years of expertise working in tutorial environments globally. This story contains code in R.

    Information pooling — what’s it?

    In most settings we’ll gather new knowledge (main knowledge assortment) or work with just one dataset that’s already accessible for evaluation. This one dataset may be from one hospital, a particular inhabitants (e.g., epidemiological research performed in a group), or a well being survey performed all through a rustic (i.e., nationally consultant well being survey…



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