Meta-Analysis for jamovi
Applied a Cox Proportional Hazards model in Python to identify prognostic factors associated with survival in pediatric candidemia patients. Estimated hazard ratios, evaluated clinical covariates, and interpreted survival outcomes.
Publication-ready research figures from a single command: forest plots, KM curves with risk tables, PRISMA 2020, ROC with DeLong — 21 chart types, 9 journal presets, Chinese support, MIT-0
Reproducible R and Python clinical trial figure templates, synthetic teaching data, independent numerical QC, and Clinical Data Lab demos.
Forest plot of Cox hazard ratios, the standard way to report which factors change patient risk.
Modular publication-figure toolkit for single-cell, spatial and clinical omics — Python (matplotlib) + R (ggplot2). Swappable themes; every panel runs on synthetic data.
Provides biomedical plotting archetypes fully interoperable with the matplotlib API.
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