Reconsidering Time Transforms in Political Survival Analysis

The standard Schoenfeld residual test for proportional hazards models is often misapplied due to arbitrary time scale choices. This article demonstrates that such decisions significantly impact research conclusions, revealing a gap between statistical practice and data realities.

New Insight Needed:

• Relying solely on the Schoenfeld test without considering specific transformations or their justification leads to potentially misleading results.
• The choice of time transformation profoundly affects model validity in political science event history studies.

Data Matters Most:

• Ignoring outlier survival times and censoring levels exacerbates misinterpretation risks.
• Simulations show that the seemingly minor decision about time scales can dramatically alter findings.

Instead of just adding a test, scholars should integrate exploratory data analysis into their modeling process. This approach provides a more robust framework for evaluating proportional hazards assumptions in event studies.