Survival Analysis - Kaplan-Meier and Cox Proportional Hazards models in Origin
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Survival Analysis

Survival Analysis is widely used in the biosciences to quantify survivorship in a population under study. OriginPro includes three widely used tests - the Kaplan-Meier (product-limit) Estimator, the Cox Proportional Hazards Model and the Weibull Fit.


Kaplan-Meier Estimator

Survial Function

Kaplan-Meier Estimator, a non-parametric estimator, uses product-limit methods to estimate the survival function from lifetime data.

In addition to estimating the survival functions, Kaplan-Meier Estimator in Origin provides three other methods to compare the survival function between two samples

  • Log Rank
  • Breslow
  • Tarone-Ware


Cox Proportional Hazard Model

The proportional hazards model, also called Cox model, is a classical semi-parameter method. It relates the time of an event, usually death or failure, to a number of explanatory variables known as covariates.


Weibull Fit

Weibull Probability
Weibull Fit report

Weibull fit is a parameter method to analyze the relationship between the survival function and the failure time. We suppose that the survival function follows a Weibull distribution and fit the model with a maximum likelihood estimation.

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