Statistical process control (SPC) requires statistical methodologies that detect changes in the pattern of data over time. The common methodologies, such as Shewhart, cumulative sum (cusum), and exponentially weighted moving average (EWMA) charting, require the in-control values of the process parameters, but these are rarely known accurately. Using estimated parameters, the run length behavior...

BACKGROUND Since 1998 BUPA has used the Short-Form 36 (SF-36) questionnaire to monitor changes in health status after adult elective surgery. Over 70 independent hospitals across the United Kingdom have collected data on over 100000 patient episodes. SF-36 is one of a number of tools that support clinical governance in the sector. Results are reported confidentially, putting the emphasis on sup...

Error: In everyday language, error is getting things wrong, usually in relation to aims and purposes [67]. There is a different technical use of the term error in statistics [27]. For statisticians, error means differences in repeated measurements. These measurement differences arise from either random variation or bias. Random variation causes inconsistent differences between measurements; bia...

In the previous two Chapters, we proposed fraction nonconforming nonparametric control charts to monitor process location and process variability. It is also shown that performance of proposed control charts are superior to that of the Shewhart X and sign charts. If process is running in an in-control state for a long period, it will reach in steady-state mode. In order to characterize long-ter...

Methods of statistical process control were briefly investigated in the field of educational measurement as early as 1999. However, only the use of a cumulative sum chart was explored. In this article other methods of statistical quality control are introduced and explored. In particular, methods in the form of Shewhart mean and standard deviation charts are introduced as techniques for ensurin...

Special Issue A Comparison of Shewhart Individuals Control Charts Based on Normal, Non-parametric, and Extreme-value Theory‡ M. B. (Thijs) Vermaat1, Roxana A. Ion2, Ronald J. M. M. Does1,3,∗,† and Chris A. J. Klaassen1,3 1Institute for Business and Industrial Statistics of the University of Amsterdam, IBIS UvA BV, Plantage Muidergracht 24, 1018 TV Amsterdam, The Netherlands 2Eurandom, PO Box 51...