Identifying dominant causes using leveraged study designs

Abstract

Dorian Shainin’s group comparison procedure is a way to find the dominant cause(s) of variation in a process, based on an investigation plan that exploits the idea of leveraging. In this paper, we study whether Shainin’s procedure is sound. Our main finding is that Shainin’s procedure is unreliable in identifying the dominant cause, and in addition, the procedure is inefficient. We propose a new efficient and sound analysis procedure based on the method of maximum likelihood. A critical evaluation shows our proposed method is superior. We also provide a tangible example and compare both methods’ outcomes.

Keywords:

• Group comparison
• method of elimination
• Red X^•
• Shainin methods
• variation reduction

Additional information

Notes on contributors

Mahsa Panahi

Mahsa Panahi is a PhD Student in the Department of Statistics and Actuarial Science. Her email address is [email protected].

Jeroen De Mast

Jeroen De Mast is Professor of Statistics at the University of Waterloo, Canada, and also Academic Director of Smart Industry at JADS in The Netherlands. His email address is [email protected].

Stefan H. Steiner

Stefan H. Steiner is Professor of Statistics at the University of Waterloo, Canada, and Chair of the Department of Statistics and Actuarial Science. His email address is [email protected].