Version Compatibility

Reference examples tested with: tableone 0.9+, statsmodels 0.14+, scikit-learn 1.4+, pandas 2.1+, numpy 1.26+. R packages cited (essential for current regulatory work): mmrm 0.3+ (Roche/openpharma), rbmi 1.5+ (Roche/Bayer via insightsengineering), gMCP, RBesT.

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures
• R: packageVersion('<pkg>') then ?function_name

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Trial Reporting Under CONSORT 2025 + ICH E9(R1)

"Prepare a clinical trial statistical report" -> Define the estimand explicitly per ICH E9(R1); execute a covariate-adjusted primary analysis targeting the right summary measure; pre-specify the missing-data strategy and run regulatory-grade sensitivity analyses; structure the output per CONSORT 2025 and the new SPIRIT 2025 alignment.

The Single Most Important Methodological Shift -- The Estimand Comes First

Kahan, Cro, Li, Harhay 2023 Am J Epidemiol 192:987 ("Eliminating Ambiguous Treatment Effects Using Estimands"): 98% of published trial reports do not describe what the reported treatment effect represents. 54% of trials: impossible to deduce the estimand from reported methods. In 74% of trials submitted for regulatory approval 1996-2017, "what-if" hypothetical effects were used but only 2 trials explained this.

The framework: ICH E9(R1) Addendum (November 2019, EMA effective 30 July 2020, FDA May 2021) defines an estimand as the precise specification of what is being estimated, via five attributes: