Missing data is a common feature of large data sets in general and medical data sets in particular. Depending on the goal of statistical analysis, various techniques can be used to tackle this problem. Imputation methods consist in substituting the missing values with plausible or predicted values so that the completed data can then be analysed with any chosen data mining procedure. In this wor...

The most concerning issues in the healthcare system will always be quality control and improvement as they are significant to health condition of patient. A statistical tool such process (SPC) charts efficient highly effective reducing sources variation within monitoring or controlling process. chart is a methodology designed evaluate change manufacturing industry being implemented gradually se...

In this paper we propose the use of statistical features for time-series classi cation. The classi cation is performed with a multi-layer perceptron (MLP) neural network. The proposed method is examined in the context of Control Chart Pattern data, which are time series used in Statistical Process Control. Experimental results verify the e ciency of the feature-based classi cation method, compa...

This paper proposes two alternative schemes for the online recognition of control chart patterns (CCPs), namely: 1 a scheme based on direct continuous recognition 2 a scheme based on ‘recognition only when necessary’. The study focuses on recognition of six CCPs plotted on the Shewhart X-bar chart, namely, random, shift-up, shift down, trend-up, trend-down and cyclic. The artificial neural netw...

This article is the first in a two-part series discussing and illustrating the application of statistical process control (SPC) to processes often examined by hospital epidemiologists. The basic philosophical and theoretical foundations of statistical quality control and their relation to epidemiology are emphasized in order to expand mutual understanding and cross-fertilization between these t...

Process control tools are a widely used approach inmany operations and production processes. Process control chart ranks as one of themost important theories used in these disciplines.This paper reviewed the bias of quality characteristicsmonitoring. Specifically, this study tries to provide a comprehensive understanding of theories of process control. The text starts with a theoretical review ...

This study investigates the statistical process control application for monitoring queue length data in M/G/1 systems. Specifically, we studied the average run length (ARL) characteristics of two different control charts for detecting changes in system utilization. First, the nL chart monitors the sums of successive queue length samples by subgrouping individual observations with sample size n....

Since the earliest days of statistical process control, it has been recognized that it is essential to monitor both mean and variability and to trigger an alarm if either characteristic shows sign of a special cause. It is, however, possible to monitor both mean and variance in a single chart responsive to shifts in either. Traditionally, this has been done by using separate X̄ and S or R charts...

Statistical process control charts are intended to assist operators of a usually stable system in monitoring whether a change has occurred in the process. When a change does occur, the control chart should detect it quickly. If the operator can also be provided information that aids in the search for the special cause, then critical off-line time can be saved. We investigate a process-monitorin...