What inspired this wish list request?
I added this to the wish list because while JMP already supports tolerance intervals for simple models and prediction intervals for mixed effects models, there’s currently no way to compute tolerance intervals for mixed effects models. This limitation is especially relevant in quality and regulatory contexts, where users need to make predictions or statements about the proportion of future outcomes. Prediction limits can be unreliable in small sample sizes.
What is the improvement you would like to see?
I would like JMP to have the option to calculate tolerance intervals (with formula included) directly from the fit model platform for mixed effects models, with the option to specify coverage and confidence. Additionally, they would be shown in the prediction profiler as well.
Why is this idea important?
Tolerance limits are important because they allow us to make probabilistic statements about the proportion of a population that falls within some specified limits, not just individual observations. They are essential in fields where quality is critical, such as pharma or medical devices. It is very important that these intervals work within the mixed effects models framework, since the a lot of data in these fields involves random effects like batches, operators, or sites, which need to be properly accounted for to ensure accurate and reliable results.