METABRIC Breast Cancer Survival and Age Data for Copula Modeling

Huma Rani published a study on April 10, 2026, comparing Frank and Clayton copula models. The work analyzes interdependencies between clinical variables, specifically overall survival and age at diagnosis, using data from the METABRIC breast cancer dataset.

Use Cases

• Modeling joint dependencies between binary survival and continuous age outcomes based on the described clinical variables.
• Comparing goodness-of-fit for different copula families based on the methodology described.
• Assessing upper tail dependence associated with favorable outcomes, as indicated by the Gumbel copula results.

Strengths

• Dataset size is 9.5 KB, indicating a focused and manageable scope.
• The study includes formal model comparison via a likelihood ratio test with a reported p-value < 0.0001.
• PIT diagnostics validated the adequacy of marginal specifications, as stated in the description.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small (9.5 KB), indicating limited scope.

Provenance

Source

figshare

Collection Method

Analysis of the METABRIC dataset using copula regression models.

Freshness

Last updated 2026-04-10 17:51:10; freshness should be verified.