Record Details


Field	Value

Title	Replication data for: Reassessing Schoenfeld Residual Tests of Proportional Hazards in Political Science Event History Analyses

Identifier	https://doi.org/10.7910/DVN/27682

Creator	Park, Sunhee Hendry, David

Publisher	Harvard Dataverse

Description	An underlying assumption of proportional hazards models is that the effect of a change in a covariate on the hazard rate of event occurrence is constant over time. For scholars using the Cox model, a Schoenfeld residual-based test has become the disciplinary standard for detecting violations of this assumption. However, using this test requires researchers to make a choice about a transformation of the time scale. In practice, this choice has largely consisted of arbitrary decisions made without justification. Using replications and simulations, we demonstrate that the decision about time transformations can have profound implications for the conclusions reached. In particular, we show that researchers can make far more informed decisions by paying closer attention to the presence of outlier survival times and levels of censoring in their data. We suggest a new standard for best practices in Cox diagnostics that buttresses the current standard with in-depth exploratory data analysis.

Subject	Social Sciences Scaled Schoenfeld residuals Proportional hazards assumption Event history analysis Replication Simulation

Contributor	David Hendry

Type	Replication and simulation code.

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