Launch the Fit Life by X platform by selecting Analyze > Reliability and Survival > Fit Life by X.
Identifies the time to event (such as the time to failure) or time to censoring. With interval censoring, specify two Y variables, where one Y variable gives the lower limit and the other Y variable gives the upper limit for each unit. For details about censoring, see the Life Distribution chapter in this guide.
Identifies censored observations. By default, 1 indicates a censored observation and 0 indicates an uncensored observation in your data table.
Identifies frequencies or observation counts when there are multiple units. If the value is 0 or a positive integer, then the value represents the frequencies or counts of observations for each row when there are multiple units recorded.
Identifies a column that creates a report consisting of separate analyses for each level of the variable.
After selecting the Censor column, select the value from the list that designates censoring. Missing values are excluded from the analysis. JMP attempts to detect the censor code and display it in the list.
Determines the relationships between the event and the accelerating factor. Examples include transformation using the following acceleration models:
If you select Location or Location and Scale, a message might appear stating that “Analysis must exclude groups that are all right censored to continue Nested Model Tests. Do you want to continue?” Click Yes to continue the analysis. Right censored groups indicate groups where all observations are right censored. The message does not appear if your sample data does not include right censored observations.
Appends a nonparametric overlay plot, nested model tests, and a multiple probability plot to the report window.
Specifies one distribution (Weibull, Lognormal, Loglogistic, Fréchet, SEV, Normal, Logistic, LEV, or Exponential distributions) at a time. Lognormal is the default setting.
Displays the method for computing confidence intervals for the parameters. The default is Wald, but you can select Likelihood instead. The Wald method is an approximation and runs faster. The Likelihood method provides more precise parameters but takes longer to compute.