Monitoring Percentiles of Proportion Data - An Application in HealthcareAbstract: Beta control charts are used for monitoring proportion data as an alternative to the standard p and np charts. These charts in general use average of proportion data to set up the control limits assuming in-control parameters known. Specific percentile of proportions may be a key quality performance measure as opposed to average for an effective process monitoring scheme. Moreover, it may be of interest to the practitioners to monitor the top or bottom percentiles of proportion data more than the other percentiles/average. In this sense, control chart based on distribution truncated suitably over the support of the random variable may be a better choice over the same with complete support. This paper considers the problem of detecting shift(s) in the percentiles of a truncated beta distributed process monitoring scheme. Performance of the proposed chart is evaluated through an application in healthcare.Length: 3 pages

Shovan, Chowdhury; Amarjit, Kundu; Bidhan, Modok

Monitoring Percentiles of Proportion Data - An Application in HealthcareAbstract: Beta control charts are used for monitoring proportion data as an alternative to the standard p and np charts. These charts in general use average of proportion data to set up the control limits assuming in-control parameters known. Specific percentile of proportions may be a key quality performance measure as opposed to average for an effective process monitoring scheme. Moreover, it may be of interest to the practitioners to monitor the top or bottom percentiles of proportion data more than the other percentiles/average. In this sense, control chart based on distribution truncated suitably over the support of the random variable may be a better choice over the same with complete support. This paper considers the problem of detecting shift(s) in the percentiles of a truncated beta distributed process monitoring scheme. Performance of the proposed chart is evaluated through an application in healthcare.Length: 3 pages

Chowdhury Shovan (), Kundu Amarjit and Modok Bidhan
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Chowdhury Shovan: Indian Institute of Management Kozhikode
Kundu Amarjit: Raiganj University
Modok Bidhan: Raiganj University

No 413, Working papers from Indian Institute of Management Kozhikode

Keywords: Average run length; Control chart; False alarm rate; Healthcare; Parametric bootstrap; Percentile; Truncated beta process (search for similar items in EconPapers)
Date: 2021-03
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