{"version":"1.0","type":"rich","title":"Gist 9674955","description":"This example simulates multi-site MRI data to test how brain volume relates to age and disease severity across two scanner sites, comparing calibration strategies for cross-site analysis. It uses a Jupyter notebook with Python, plotting the simulated relationships through matplotlib and seaborn, and applies ordinary least squares and robust linear models via the statsmodels API. The notebook defines governing equations with parameters like scanner scaling and offset, then generates synthetic control and patient cohorts to evaluate how site effects and EDSS scores influence brain volume estimates.","provider_name":"VizHub AI Studio","provider_url":"https://next.vizhub.com","html":"<iframe src=\"https://next.vizhub.com/viz/gist-9674955?mode=embed\" width=\"960\" height=\"500\" scrolling=\"no\" frameborder=\"1\"></iframe>","width":960,"height":500,"cache_age":3600}