JMP analyzes survival data using methods that handle survival times with non-normal distributions and censored data.
Presenter: Jian Cao
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Advanced Mastering JMP: Analyzing Survival Data
Survival Data Analysis Overview and Using Kaplan-Meier Estimates to Understand Medical Data
Get an overview of when and why survival analysis is useful, and see how to perform survival analysis. The presenter uses data from medical studies to analyze survival using the Life Distribution and Survival platforms in JMP. He examines Kaplan-Meier estimates and compares survival by grouping variables. He also shows how to run parametric survival models to predict survival times based on type of treatment.
Using Parametric Survival Models to Understand Medical Data
The presenter uses medical studies data to demonstrate the use of parametric survival models and Cox’s Proportional Hazards Model. He compares models, uses the Distribution Profiler to predict survival probability and uses the Quantile Profiler to identify median survival time.
Using Survival Models to Understand Customer Data
The presenter uses customer data to determine the drivers of customer attrition (churn) and predict the expected customer retention duration.
Resources mentioned in these videos
- The Statistical Analysis of Failure Time Data, Second Edition by John D. Kalbfleisch, Ross L. Prentice