Colleen McKendry, Senior Statistical Writer, JMP
This presentation is an extension of the talk, "Measurement Systems Analysis for Curve Data Using Functional Random Effects Models," presented at JMP Discovery Europe 2023. Here, a functional random effects model was used to perform a Functional Gauge R&R analysis on data that contained a set of curves as the response. In this application, the functional model was expanded using the eigenfunctions and then was expressed as a random effects model, where variance components were estimated using standard methods. This analysis was done using the Functional Data Explorer and Fit Mixed platforms.
In the updated version of this presentation, I show that it is possible to include fixed effects in this type of analysis using the same model expansion approach. The functional model is still expanded using the eigenfunctions but is expressed as a generalized mixed model instead. I also discuss ideas for utilizing wavelet expansion as opposed to eigenfunction expansion and how this could improve model fits for certain types of data.
