I watched Hyde Miller-san's tutorial video for JMP17's MSA with my colleagues at JMP Japan office.
We have three questions about AIAG's Gauge R&R on JMP.
(1) On page.196 in AIAG(2010:4th ed.) Measurment System Analysis Reference Manual(4th ed.), it's said that "For analysis purposes, the negative variance component is set to zero". Does this sentece mean which of the followings?
- (a) You just set zero only for negative variance estimates, and calculate Gauge R&R indicies without changing positive variance estimates,...or...
- (b) You remove the components which has negative variance estimates, and refit the model.
(2)What kind of estimation method is used in JMP17's AIAG Gauge R&R Results on the EMP MSA platform?
Is the method REML/EMS *?
* If data is balanced and there is no negative variance, then EMS is used. Othewise, REML is used.
(3) I personally and intuitively think Bayesian analysis is generally better for MSA (because the sample size is not large in MSA study, and we can avoid negative estimates in Bayesian analysis). Is there a formal guideline or an academic refereed paper in which Bayesian analysis is recommended for MSA and/or Gauge R&R?
