Book Review: Design and Analysis of Gauge R&R Studies

Design and Analysis of Gauge R&R Studies: Making Decisions with Confidence Intervals in Random and Mixed Anova Models (ASA-SIAM Series on Statistics and Applied Probability)

by Richard K. Burdick, Connie M. Borror, Douglas C. Montgomery

ASA-SAM Series on Statistics and Applied Probability 2005



An applied Statistician, or someone who needs an in-depth understanding of the statistical calculations used in analyzing ANOVA Gauge R&R Studies with Confidence Intervals.
To get the most from this book, you should have an good understanding of Analysis of Variance, and Confidence Intervals.


The authors start with a review of the Capability Measures used to assess a Measurement System. They reference the AIAG MSA Guidelines, and extend their review to take into account Confidence Intervals. They use a very neat graphical method to illustrate the capability of a Measurement System with Confidence Intervals.
There are a number of problems associated with the traditional Measurement Capability Indices, such as Precision To Tolerance Ratio and Number of Distinct Categories, so the authors favour the use of Misclassification Rates as the criteria to assess a system.

Most of the book shows how to do the appropriate ANOVA Gage R&R Calculations in various situations – for example – a single operator, multiple operators, dedicated operators etc – See the Table of Contents below.
This is not a conceptual book – It is at the opposite end of the spectrum to Concepts for R&R Studies

The authors dedicate Chapter 4 – Design of Gauge R&R Experiments – to give some practical guidelines for how to set up and run a study. They also cover how to assess the statistical validity of a study using residual plots.



Excellent and detailed review of Gauge R&R ANOVA Techniques


Buy this book if you are pretty good on statistics (ANOVA), and would like a ‘statistical cookbook’ that shows you how to analyze various R&R Studies using the appropriate ANOVA Techniques, taking into account Confidence Intervals.

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  1. Introduction
  2. Balanced One-Factor Random Models
  3. Balanced Two-Factor Crossed Random Models with Interaction
  4. Design of Gauge R&R Experiments
  5. Balanced Two-Factor Crossed Random Models with No Interaction
  6. Balanced Two-Factor Crossed Mixed Models
  7. Unbalanced One- and Two-Factor Models
  8. Strategies for Constructing Intervals with ANOVA Models


A The Analysis of Variance
B MLS and GCI Methods
C Tables of F-Values

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