The research aimed to study a health evaluation method from the annual health examination by an application of testing fuzzy hypotheses. The fuzzy p-value is used for the testing. The reason that we need to apply the fuzzy hypotheses testing, because classical hypotheses testing can not test the difference between a population mean with an interval of constant. The participants were 136 recipients who had an annual health examination in Ubon Rachathani Rajabhat University in 2015. Research instrument was the simplified forms with result recorded from a laboratory examination in an annual health examination. Statistics used in data analysis were testing fuzzy hypotheses by using fuzzy p-value and percentage. The method of health diagnosis was the testing fuzzy hypotheses by using fuzzy p-value consisted of the followings : 1) Set the fuzzy hypotheses to insist the results from laboratory in the annual health examination. 2) Set fuzzy significant level. 3) Define the test statistic. 4) Finding the fuzzy p-value. 5) Compare the fuzzy p-value with the fuzzy significant and 6) Make decision. Most of the results from laboratory in annual health examination were in normal value with degree 0.8627-1.0. The study indicated that the values of cholesterol was higher than normal value with degree 1.
Arnold, B. F. (1998). Testing fuzzy hypotheses with crisp data. Fuzzy Set Syst, 94, 323-333.
Buckley, J. J. (2005). Fuzzy statistics: hypothesis testing. Soft Computing, 9(7), 512-518.
Chaiear, N., & Karusun, N. (2007). Is an annual examination necessary. Esan Madicine Journal, 3, 170-182.
Casals, M. R., Gil, M. A., & Gil, P. (1986). On the use of Zadeh's probabilistic definition for testing statistical hypotheses from fuzzy information. Fuzzy Sets and Systems, 20(2), 175-190.
Denoeux, T., Masson, M. H., & Hébert, P. A. (2005). Nonparametric rank-based statistics and significance tests for fuzzy data. Fuzzy Sets and Systems, 153(1), 1-28.
Filzmoser, P., & Viertl, R. (2004). Testing hypotheses with fuzzy data: The fuzzy p-value. Metrika, 59(1), 21-29.
Geyer, C. J., & Meeden, G. D. (2005). Fuzzy and randomized confidence intervals and p-values. Statistical Science, 20(4), 358-366.
Holena, M. (2001). A fuzzy-logic generalization of a data mining approach. Neural Network World, 11(6), 595-610.
Holena, M. (2004). Fuzzy hypotheses testing in the framework of fuzzy logic. Fuzzy Sets and Systems, 145(2), 229-252.
Karusun, N., Sawanyavisuth, K., & Chaiear, N. (2005). Health status of health care worker at Srinagarind Hospital: experience from the annual health check-up program. J Med Assoc Thai, 88(11), 1619-1623.
Parchami, A., Ivani, R., & Mashinchi, M. (2011). An application of testing fuzzy hypotheses: Soil study on the bioavailability of cadmium. Scientia Iranica, 18(3), 470-478.
Parchami, A., & Mashinchi, M. (2008). Testing fuzzy hypotheses with crisp data: the minimax approach: Proceeding of the 2nd Joint congress on fuzzy and Intelligent System (p. 5). Tehran, Iran: Maleke-Ashtar University.
Regional Health Promotion Center 7 Ubon Rachathani. (2016). Health record booklet. Ubon Rachathani, TH.
Supason, W. (2008). Perception of annual health examination among people in Khok Chan Subdistrict Trakan Phuet Phon District Ubon Ratchatani Province. Chiang Mai: Chiang Mai University.
Taheri, S. M. (2003). Trends in fuzzy statistics. Aust J Stat, 32(3), 239-257.
Taheri, S. M., & Behboodian, J. (1999). Neyman-Pearson Lemma for fuzzy hypotheses testing. Metrika, 49(1), 3-17.
Taheri, S. M., & Behboodian, J. (2001). A Bayesian approach to fuzzy hypotheses testing. Fuzzy Sets and Systems, 123(1), 39-48.
Tanaka, H., Okuda, T., & Asai, K. (1979). Fuzzy information and decision in a statistic model. In: Gupta MM et al. (ed) Advances in fuzzy set theory and application. North-Holland, Amsterdam, 303-320.
Watanabe, N., & Imaizumi, T. (1993). A fuzzy statistical test of fuzzy hypotheses. Fuzzy Sets and systems, 53(2), 167-178.
Yuan, Y. (1991). Criteria for evaluating fuzzy ranking methods. Fuzzy sets and Systems, 43(2), 139-157.
Zadeh, L. A. (1965). Information and control. Fuzzy sets, 8(3), 338-353.
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