Replication data for: Reassessing Schoenfeld Residual Tests of Proportional Hazards in Political Science Event History Analyses
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. 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 i' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Event history analysis","Proportional hazards assumption","Replication","Scaled Schoenfeld residuals","Simulation"]} <|eot_id|>
 Here is the Description of a dataset. 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 i' . Please return only a json list of at most 3 Keywords corresponding to the 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 i
Event history analysis; Proportional hazards assumption; Replication; Scaled Schoenfeld residuals; Simulation