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Issue title: Selected papers from the 4th Iranian Joint Congress On Fuzzy and Intelligent Systems – CFIS2015, 9–11 September 2015
Article type: Research Article
Authors: Taheri, S. Mahmouda | Salmani, Fatemehb | Abadi, Alirezab; * | Majd, Hamid Alavib
Affiliations: [a] Faculty of Engineering Science, College of Engineering, University of Tehran, Tehran, Iran | [b] Department of Biostatistics, Faculty of Paramedical Sciences, ShahidBeheshti University of Medical Sciences, Tehran, Iran
Correspondence: [*] Corresponding author. Alireza Abadi, Department of Biostatistics, Faculty of Paramedical Sciences, ShahidBeheshti University of Medical Sciences, Tehran, Iran. Tel.: +98 21 2387 2567 8; Fax: +2243 9936; Phone: 9121374416; E-mail: alirezaabadi@gmail.com.
Abstract: Longitudinal study is type of studies that researchers visit subject in several time. Therefore, there are observations of the same subjects that are correlated. These types of studies are widely used in medical science. On the other hand, in medical studies, we frequently face situations that response mastered by linguistic terms. A new transition model which will be able to handle correlation between fuzzy responses is introduced. In this paper we model the transition possibility by fuzzy logistic regressions, and representing how the covariates relate to changes in response. With p covariates, there are (p + 1) parameters including intercepts, which we estimate by extended least squares method. These possibilities depend on the covariates. By using a real data set, an applied example is provided to explain the applicability of the proposed model in clinical studies. In the clinical studies, the effect of hydro-alcoholic extract of Urtica Dioica on menorrhagia (for which the status is basically expressed by linguistic/fuzzy terms) is investigated also the effect of mental intervention in recovery of patients with Lichen Planus disease.
Keywords: Fuzzy data, longitudinal study, transition model, fuzzy logistic regression, possibilistic odds
DOI: 10.3233/IFS-152040
Journal: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 3, pp. 1265-1273, 2016
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