ENBIS: European Network for Business and Industrial Statistics

EWMA Control Charts for Monitoring Binary Processes with Applications to Medical Diagnosis Data

22 September 2009, 16:35 – 16:55

Abstract

Submitted by

Christian Weiß

Authors

Christian H. Weiß, University of Würzburg, Institute of Mathematics, Department of Statistics, Germany. Martin Atzmüller, University of Würzburg, Institute of Computer Science, Department of Artificial Intelligence, Germany.

Abstract

The statistical control of attribute data processes is an area of emerging interest both in research and professional practice. Often one is concerned with binary attribute processes. The traditional example for such binary quality characteristics is the case, where the process describes the result of an inspection of an item, taking the value 1 iff the item was defective or nonconforming. The presented research, however, was motivated by a non-manufacturing example: medical diagnosis data.

To monitor a binary process, exponentially weighted moving average (EWMA) control charts in different variations are proposed. The ARL performance of the EWMA approach both with standard and with skewness-corrected 3-Sigma control limits is investigated and design recommendations are derived. The proposed EWMA control charts are applied to medical diagnosis data taken from the diagnostic expert system SonoConsult in order to provide a semi-automatic component for monitoring the documentation behavior of different examiners.

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