Data considerations for Distribution ID Plot (Arbitrary Censoring)

To ensure that your results are valid, consider the following guidelines when you collect data, perform the analysis, and interpret your results.

The data that you collect are usually failure times
For example, you might collect failure times for units that are tested at a specific temperature. You might also collect samples of failure times under different temperatures, or under different combinations of stress variables. Alternatively, the data might measure product usage in units other than time, such as the amount of mileage for a tire until it fails.
Your data must be arbitrarily censored
To be considered arbitrarily censored, your data should include either left-censored observations (you know only the time before which the failure occurred) or interval-censored observations (you know only the times between which the failure occurred). Your data could also have a varied censoring scheme that includes exact failure times, right censoring, left censoring, and interval censoring. However, if your data consist of only exact failure times and/or right-censored observations (you know only the time after which the failure occurred), use Distribution ID Plot (Right Censoring). For more information on censored data, go to Data censoring.
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