For the latest version of JMP Help, visit JMP.com/help.

Reliability and Survival Methods > Fit Parametric Survival > The Parametric Survival Fit Report
Publication date: 09/28/2021

The Parametric Survival Fit Report

If you select All Distributions in the launch window, a Parametric Survival Fit report appears for each distribution. If you specify a Cause column in the launch window, a Parametric Survival Fit report appears for each cause. Otherwise, only one Parametric Survival Fit report appears. Each Parametric Survival Fit report contains the following:

Effect Summary

Shows an interactive report that enables you to add or remove effects from the model. See Effect Summary Report in Fitting Linear Models.

Model Fit Details

The Time to event shows which Y column is specified, and the Distribution shows which distribution is fit. AICc, BIC, and -2Loglikelihood are all measures of the model fit. These measures allow for comparisons to other model fits. Observation Used and Uncensored Values are summary statistics for the data. See Likelihood, AICc, and BIC in Fitting Linear Models.

Whole Model Test

Compares the complete fit with an intercept-only fit. If there is only an intercept term, the fit is the same as that from the Life Distribution platform.

Parameter Estimates

Shows the estimates of the regression parameters.

Image shown hereA link to launch the Generalized Regression platform appears below the Parameter Estimates table. The link enables you to perform variable selection using the Generalized Regression platform and appears under the following circumstances:

The model has no scale effects.

No Cause column is specified in the launch window.

The Distribution specified in the launch window is Normal, Lognormal, or Weibull.

Alternate Parameterization

(Available only for the Weibull distribution.) Shows the parameter estimates for the α and β parameterization of the Weibull distribution. For more information about this parameterization, see Weibull.

Wald Tests

Shows a Wald Chi-square test for each term in the model.

Effect Likelihood Ratio Tests

Compare the log-likelihood from the fitted model to one that removes each term from the model individually.

Plot Survival Quantiles

Shows the data points plotted with the 0.1, 0.5, and 0.9 quantiles.

Figure 14.5 The Parametric Survival Fit Report 

The Parametric Survival Fit Report

Want more information? Have questions? Get answers in the JMP User Community (community.jmp.com).