机器学习
R Statistics & Modeling
Use when performing statistical modeling, hypothesis testing, or model diagnostics in R. Provides expert guidance on linear models, GLMs, mixed models, survival analysis, Bayesian methods, time series, model comparison, assumption checking, and effect-size reporting. Triggers: statistical model, hypothesis test, regression, ANOVA, t-test, chi-squared, lm, glm, mixed model, survival analysis, p-value, confidence interval, diagnostics, significantly different, statistical test, odds ratio, effect size, model assumptions, Cox model. Do NOT use for machine learning or predictive modeling — use r-tidymodels instead. Do NOT use for clinical trial-specific analysis — use r-clinical instead.