This article proposes an algorithm for deploying manpower (equipped with adequate measuring instrument) to an ¯¯¯X&S control chart scheme so that the resultant control chart (referred to as ¯¯¯X&S M-chart) minimizes the expected total cost incurred in the implementation of the Statistical Process Control (SPC).
This type of analysis accounts for variability in intervention implementation, which increases the statistical power to detect significant effects [ 133], facilitates a dose-response relationship, and enhances the clinical relevance of the study results [ 127].
HMOvS initiated the study, participated in the design, coordinated the implementation of the study, participated in the statistical analysis and was the primary writer of the manuscript.
SD conceived and designed the study, supervised its implementation, namely data collection, helped in the statistical analysis and helped to write the manuscript.
The major appeal of this distribution is its hazard behavior, which includes all four basic hazard shapes (increasing, decreasing, bathtub, and arc-shaped), as well as its ready implementation in standard statistical software packages.
Automatic variable selection methods, including forward selection, backward elimination, and stepwise selection (hereafter, 'stepwise methods') [ 6, 7] were developed in 1960s and gained popularity in epidemiology and other fields for a number of reasons, including computational simplicity, relative ease of interpretation, and their implementation in major statistical software packages [ 3].
YK and DA–Z participated in the design of the study and coordinated its implementation, and performed the statistical analysis.
