Analysis of Performance Measures in Experimental Designs Using Jackknife

Abstract

Experimental designs with performance measures as responses are common in industrial applications. The existing analysis methods often regard performance measures as sole response variables without replicates. Consequently, no degrees of freedom are left for error variance estimation in these methods. In reality, performance measures are obtained from replicated primary-response variables. Precious information is hence lost. In this paper, we suggest a jackknife-based approach on the replicated primary responses to provide an estimate of error variance of performance measures. The resulting tests for factor effects become easy to construct and more reliable. We compare the proposed method with some existing methods using two real examples and investigate the consistency of the jackknife variance estimate based on simulation studies.

• Lenth's Method
• Performance Measure
• Pseudo Standard Error
• Unreplicated Factorial Experiments

Additional information

Notes on contributors

Asokan Mulayath Variyath

Mr. Variyath is a PhD Student in the Department of Statistics and Actuarial Science. He is a member of ASQ. His email address is [email protected].

Bovas Abraham

Dr. Abraham is a Professor in the Department of Statistics and Actuarial Science. He is a Fellow of ASQ. His email address is [email protected].

Jiahua Chen

Dr. Chen is a Professor in the Department of Statistics and Actuarial Science, University of Waterloo and Department of Statistics, Nankai University. His email address is [email protected].