Gist d4b2a37f3ec9a90469c8

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Gist d4b2a37f3ec9a90469c8

✓ Published0🌍 Public

Last edited Dec 10, 2015

Created on Dec 10, 2015

This visualization simulates longitudinal brain-imaging measurements across multiple subjects and time points, showing how percentile values (e.g., MTR_25) vary and are modeled with ordinary least squares regression per subject. It first computes subject means, average standard deviations, and true beta coefficients from the input CSV, then generates synthetic data for three time points using normal distributions. The code relies on pandas for data manipulation, statsmodels formula API for OLS fitting, numpy for random sampling, and seaborn for plotting.

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