Application of the multiple dependent state sampling strategy to late adolescent suicide rates
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Date
2023
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Science and Business Media LLC
Abstract
A multiple dependent state sampling plan (MDSSP) is designed when the lifetimes of the variables follow New Lomax Rayleigh Distribution (NLRD). The decision to accept or reject a lot in the proposed methodology is based on the quality of the given present or previous lots. A binomial model-based operating characteristic curve (OC curve) for continuous lots of variables under similar settings in healthcare is used in finding the probability of acceptance, acceptance number, rejection number, and the number of preceding (succeeding) lots to consider. Time truncated life test based on the specified median of the NLRD is used in designing the current acceptance sampling plan. For specified values of the parameters of NLRD, quantile ratios, consumer’s risk and producer’s risk, average sampling number (ASN) and probability of acceptance of a lot are reported in tables. Real data on worldwide suicide rates of 15–19 years in the year 2019 from the World Health Organization (WHO) website is considered to illustrate this methodology. The minimum sample size required from the selected data to comment on worldwide suicide rates in late adolescents is explained with MDSSP. The results of the proposed acceptance sampling method are compared with the single-stage sampling plan.
Description
Abstract. Full text available at http://dx.doi.org/10.1186/s12874-023-02007-2
Keywords
Adolescent, Humans, World Health Organization, Probability, *Suicide, *Models, Statistical, Average sample number, Health care quality indicators, Multiple dependent state sampling plan, New Lomax Rayleigh distribution, Quality gap analysis in hospitals, Sample Size, Suicide rates of late adolescents
Citation
Kolli, N., Rosaiah, K., Rao, G. S., & Kirigiti, P. J. (2023). Application of the multiple dependent state sampling strategy to late adolescent suicide rates. BMC medical research methodology, 23(1), 192.