Comprehensive statistical modeling skill for fitting regression models, survival models, and mixed-effects models to biomedical data. Produces publication-quality statistical summaries with odds ratios, hazard ratios, confidence intervals, and p-values.
✅ Linear Regression - OLS for continuous outcomes with diagnostic tests ✅ Logistic Regression - Binary, ordinal, and multinomial models with odds ratios ✅ Survival Analysis - Cox proportional hazards and Kaplan-Meier curves ✅ Mixed-Effects Models - LMM/GLMM for hierarchical/repeated measures data
✅ ANOVA - One-way/two-way ANOVA, per-feature ANOVA for omics data ✅ Model Diagnostics - Assumption checking, fit statistics, residual analysis ✅ Statistical Tests - t-tests, chi-square, Mann-Whitney, Kruskal-Wallis, etc.
对生物医学数据集执行统计建模和回归分析。支持线性回归、逻辑回归(二元/序数/多项)、混合效应模型、Cox 比例风险生存分析、Kaplan-Meier 估计和综合模型诊断。提取比值比、风险比、置信区间、p 值和效应大小。旨在解决涉及临床/实验数据的 BixBench 统计推理问题。当要求拟合回归模型、计算优势比、执行生存分析、运行统计测试或解释所提供数据的模型系数时使用。 来源:mims-harvard/tooluniverse。