Produces tests that compare the log likelihood from the fitted model to one that removes each term from the model individually.
Calculates a profile-likelihood 95% confidence interval on each parameter and lists them in the Parameter Estimates table.
Produces a correlation matrix for the model effects with each other and with the parameter of the fitting distribution.
Produces a covariance matrix for the model effects with each other and with the parameter of the fitting distribution.
Specify regressor 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.
Specify regressor 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 95%.
Shows a plot with the residuals on the x-axis and the Kaplan-Meier estimated quantiles on the y-axis. In cases of interval censoring, the midpoint is used. The residuals are the simplest form of Cox-Snell residuals, which convert event times to a censored standard Weibull or other standard distribution.
Shows the response surfaces of the failure probability versus individual explanatory and response variables. See the Profilers book.
Shows the response surfaces of the response variable versus the explanatory variable and the failure probability. See the Profilers book.
Shows three probability plots for assessing model fit. The plots show different lines for each combination of the X levels.
Separate Location is a probability plot assuming equal scale parameters and separate location parameters. This is useful for assessing the parallelism assumption.
Separate Location and Scale is 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 is a probability plot for which the distribution parameters are functions of the X variables.
Saves the estimated quantile formula to a new column in the data table. Selecting this option displays a popup dialog, asking you to enter a probability value for the quantile of interest.