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Survival Analysis
Survival analysis deals with time to an event in systems. Events can be death in biological systems and failure in technical systems, but the event may be something entirely different, such as divorce, relapse of a disease, or an insurance claim. Often the time to an event is not known exactly, but is known to fall in some interval; this is called censoring.
Mathematica allows you to specify time-to-event data in a flexible (censor intervals, indicators, or counts) and powerful (right, left, interval censoring, and truncation) way. Time-to-event data is broadly supported throughout the system. Time-to-event data can be used to compute descriptive statistics, estimate parametric and nonparametric distributions, fit a variety of survival models, and perform hypothesis tests.
Featured Examples |
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Baboon Descent Times
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Compare Nonparametric and Parametric Reliability Models
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Compare Survival Rates of Treatment and Control Groups
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Compare Two Models of Wind Speeds
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Compute Statistics from Censored and Truncated Data
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Estimate Confidence Limits and Bands
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Estimate Distribution Parameters from Survival Data
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Estimate Expected Survival with Incomplete Data
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Estimate the Induction Time Distribution for a Disease
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Experimental Drug Efficacy
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Fit Nonparametric Distributions to Survival Data
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Quantify Relative Risk Using a Cox-Proportional Hazards Model
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Time to Retraction for Breast Cancer Patients
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Use a Gompertz Distribution as a Lifetime Model
