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Research conducted with synthetic datasets facilitates sharing of data to ensure reproducability and transparency. A function based on our work on adherence trajectories or other approaches (e.g. Dahmen, Jessamyn, and Diane Cook. "SynSys: A Synthetic Data Generation System for Healthcare Applications." Sensors 19.5 (2019): 1181. see also github repository) could create synthetic data based on an input dataset, e.g.
synthetic_date <- create_synthetic_data(data, ID.colnames, disp.date.colname, duration.colname, medication.class.colnames, daily.dose.colname, sample.size, follow.up.window.duration)
with:
The function output would be a synthetic dataset of the desired size and duration with some diagnostic output, e.g. data similarity measures.
The text was updated successfully, but these errors were encountered:
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Research conducted with synthetic datasets facilitates sharing of data to ensure reproducability and transparency. A function based on our work on adherence trajectories or other approaches (e.g. Dahmen, Jessamyn, and Diane Cook. "SynSys: A Synthetic Data Generation System for Healthcare Applications." Sensors 19.5 (2019): 1181. see also github repository) could create synthetic data based on an input dataset, e.g.
with:
The function output would be a synthetic dataset of the desired size and duration with some diagnostic output, e.g. data similarity measures.
The text was updated successfully, but these errors were encountered: