Parametric survival curves can be used when a distribution of failure time can be supposed. Run all your survival analyses in Excel using the XLSTAT software.
What is Parametric survival curve analysis
The Parametric survival curve belongs to the descriptive methods of survival analysis, as does life table analysis.
Parametric survival curves allows you to quickly obtain a population survival curve and essential statistics such as the median survival time based on a parametric distribution.
The Parametric survival curves is an alternative to Kaplan-Meier analysis when a distribution of the failure time can be supposed.
Use of Parametric survival curves
Parametric survival curve is used to analyze how a given population evolves with time. This technique is mostly applied to survival data and product quality data. There are three main reasons why a population of individuals or products may evolve: some individuals die (products fail), some other go out of the surveyed population because they get healed (repaired) or because their trace is lost (individuals move from location, the study is terminated, among other reasons). The first type of data is usually called failure data, or event data, while the second is called censored data.
Results for the Parametric survival curve in XLSTAT
Parametric survival curves tables
The parameters of the chosen distribution (generally the Weibull distribution) are displayed together with standard error, p-values and confidence intervals.
The quantiles associated to the distribution and to the data are also displayed.
Charts for Parametric survival curves
XLSTAT offers the following charts:
- Survival distribution function (SDF)
- -Log(SDF) corresponding to the –Log() of the survival distribution function (SDF).
- Log(-Log(SDF)) corresponding to the Log(–Log()) of the survival distribution function.
- Hazard function.