Living With Survival Analysis in Orthopedics

Cynthia S. Crowson, Dirk R. Larson, Katrina L. Devick, Elizabeth J. Atkinson, Carly S. Lundgreen, David G. Lewallen, Daniel J. Berry, Hilal Maradit Kremers

Research output: Contribution to journalArticlepeer-review


Time to event data occur commonly in orthopedics research and require special methods that are often called “survival analysis.” These data are complex because both a follow-up time and an event indicator are needed to correctly describe the occurrence of the outcome of interest. Common pitfalls in analyzing time to event data include using methods designed for binary outcomes, failing to check proportional hazards, ignoring competing risks, and introducing immortal time bias by using future information. This article describes the concepts involved in time to event analyses as well as how to avoid common statistical pitfalls. Please visit the following and for videos that explain the highlights of the paper in practical terms.

Original languageEnglish (US)
Pages (from-to)3358-3361
Number of pages4
JournalJournal of Arthroplasty
Issue number10
StatePublished - Oct 2021


  • Cox model
  • censoring
  • survival analysis
  • time-to-event analysis
  • total joint arthroplasty

ASJC Scopus subject areas

  • Orthopedics and Sports Medicine


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