Tolerance interval "censored data"/"over detection limit"Hi
I am running a test on the yield strength of some material, but due to some limitations in the measurement setup, I can not run the test until the specimens break. I.e. for example I can only run the test up to an applied force of 1kN. This means I can not find the actual yield strength and its distribution, I only know that I have a number of samples, N, that can take over 1kN of force.
Is there method to estimate a tolerance interval for this type of data?
Your input is much appreciated.
AnalyticsRe: Tolerance interval "censored data"/"over detection limit"You have several challenges:
1. You cannot separate measurement error from the product variation
2. Since your data is truncated it will be difficult to get an estimate of central tendency or dispersion.
You could think about the test as a go/no-go (treat the response variable as nominal) and estimate probabilities of failure. Can you apply a constant force (<1kN) and measure some other characteristic of the material (changes in material properties like elongation)?
Re: Tolerance interval "censored data"/"over detection limit"I am wondering if it is possible to treat this with a proportional hazards model, with the force strength treated as if it were the time variable. In other words, rather than data censored by time to event, it would be analyzed as force applied to event. In both cases, the data is censored in that some observations (perhaps many) will not have the event at the end point (either time or force applied). I have no idea if this is a legitimate approach, but the situations seem analogous.
