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Analysis of Lifetime Data

Nonparametric and semiparametric methods for analyzing reliability and survival data


coxphfit Cox proportional hazards regression
ecdf Empirical cumulative distribution function
ecdfhist Histogram based on empirical cumulative distribution function
ksdensity Kernel smoothing function estimate for univariate and bivariate data
mle Maximum likelihood estimates
mlecov Asymptotic covariance of maximum likelihood estimators
fitdist Fit probability distribution object to data
dfittool Open Distribution Fitting app
linhyptest Linear hypothesis test
evfit Extreme value parameter estimates
expfit Exponential parameter estimates
gamfit Gamma parameter estimates
lognfit Lognormal parameter estimates
normfit Normal parameter estimates
probplot Probability plots
wblfit Weibull parameter estimates
wblplot Weibull probability plot

Examples and How To

Survivor Functions for Two Groups

This example shows how to find the empirical survivor functions and the parametric survivor functions using the Burr type XII distribution fit to data for two groups.

Hazard and Survivor Functions for Different Groups

This example shows how to estimate and plot the cumulative hazard and survivor functions for different groups.

Cox Proportional Hazards Model for Censored Data

This example shows how to construct a Cox proportional hazards model, and assess the significance of the predictor variables.


What Is Survival Analysis?

Survival analysis is time-to-event analysis, that is, when the outcome of interest is the time until an event occurs.

Kaplan-Meier Method

Use the Kaplan-Meier nonparametric method to estimate the empirical hazard, survivor, and cumulative distribution functions.

Cox Proportional Hazards Regression

Cox proportional hazards regression is a semiparametric method for adjusting survival rate estimates to quantify the effect of predictor variables.

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