Worksheets and research resources · Page 27
Search and filter all worksheets and research resourcesStan Bayesian modeling software
Access open-source Bayesian modeling software, documentation and diagnostic guidance. Model specification, prior choices and computation checks remain essential.
Project Jupyter notebooks
Use free open-source notebook software and documentation to combine analysis code, results and explanations. Hosted computing services may have separate charges.
statsmodels statistical modeling
Explore open-source Python models, tests, diagnostics and worked examples. Check model assumptions and the documentation for the version used in your analysis.
SciPy scientific computing
Access free open-source scientific-computing algorithms and reference documentation, including statistical distributions, optimization and numerical integration.
seaborn statistical graphics
Use open-source Python tools, tutorials and examples for distribution, categorical and relationship plots. Plot defaults still require thoughtful interpretation.
scikit-learn model evaluation
Read free documentation and use open-source tools for preprocessing, predictive modeling and model evaluation. Validation design and data leakage need explicit checks.
WHO ICTRP trial-search guidance
Find official guidance for searching trial-registration records from participating registries worldwide. Registry records are not clinical evidence appraisal or regulatory approval.
Covariate balance diagnostic plan
Record fixed standardization choices, distribution checks and remaining confounding concerns.
Logistic interaction scenario specification
Document coding, covariate profiles and probability-scale contrasts before interpreting an interaction.
Survival risk-set reconciliation worksheet
Audit time ordering, risk-set transitions and product-limit arithmetic with explicit censoring and entry rules.
Simulation probability precision plan
Specify replicate success, failure handling and Monte Carlo precision before running a simulation study.
Missing binary outcome sensitivity bounds
Define a binary estimand and audit deterministic extreme-case bounds without mistaking them for confidence intervals.