Publication date: 07/30/2020

The Parametric Survival Fit red triangle menu contains the following options:

Likelihood Ratio Tests

Produces tests that compare the log-likelihood from the fitted model to one that removes each term from the model individually.

Wald Tests

Produces chi-square test statistics and p-values for Wald tests of whether each parameter is zero.

Likelihood Confidence Intervals

Specifies the type of confidence intervals shown in the Parameter Estimates table for each parameter. When this option is selected, a profile likelihood confidence interval appears. Otherwise, a Wald interval is shown. In the report, the interval type is noted below the Parameter Estimates table. This option is on by default when the computational time for the profile likelihood confidence intervals is not large.

Note: You can change the α level for the confidence intervals by selecting Set Alpha Level from the red triangle menu in the Fit Model launch window. The default α level is 0.05.

Correlation of Estimates

Produces a correlation matrix for the model effects with each other and with the parameter of the fitting distribution.

Covariance of Estimates

Produces a covariance matrix for the model effects with each other and with the parameter of the fitting distribution.

Estimate Survival Probability

Specify effect values and one or more time values. JMP then calculates the survival and failure probabilities with 95% confidence limits for all possible combinations of the entries.

Estimate Time Quantile

Specify effect values and one or more survival values. JMP then calculates the time quantiles and 95% confidence limits for all possible combinations of the entries.

Note: For the Estimate Survival Probability and Estimate Time Quantile options, you can change the alpha level from the default of 0.05.

Residual Probability Plot

Shows a probability plot of the standardized residuals.

Save Residuals

Saves the residuals to a new column in the data table. For interval-censored observations, two columns of residuals are saved to the data table.

Distribution Profiler

Shows the response surfaces of the failure probability versus individual explanatory and response variables.

Quantile Profiler

Shows the response surfaces of the response variable versus the explanatory variable and the failure probability.

Distribution Plot by Level Combinations

Shows three probability plots for assessing model fit. The plots show different lines for each combination of the X levels.

Separate Location

A probability plot assuming equal scale parameters and separate location parameters. This is useful for assessing the parallelism assumption.

Separate Location and Scale

A probability plot assuming different scale and location parameters. This is useful for assessing if the distribution is adequate for the data. This plot is not shown for the Exponential distribution.

Regression

A probability plot for which the distribution parameters are functions of the X variables.

Save Probability Formula

Saves the estimated probability formula to a new column in the data table.

Save Quantile Formula

Saves the estimated quantile formula to a new column in the data table. Selecting this option displays a pop-up dialog, asking you to enter a probability value for the quantile of interest.

Publish Probability Formula

Creates a probability formula and saves it as a formula column script in the Formula Depot platform. If a Formula Depot report is not open, this option creates a Formula Depot report. See Formula Depot in Predictive and Specialized Modeling.

Publish Quantile Formula

Creates a quantile formula and saves it as a formula column script in the Formula Depot platform. If a Formula Depot report is not open, this option creates a Formula Depot report. See Formula Depot in Predictive and Specialized Modeling.

Model Dialog

Relaunches the launch window.

Effect Summary

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

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