A Modification to the Fuzzy Regression Discontinuity Model to Settings with Fuzzy Variables
A Modification to the Fuzzy Regression Discontinuity Model to Settings with Fuzzy Variables作者机构：Department of Mathematics The Pan African University Institute for Basic Sciences Technology and Innovation (PAUSTI) Nairobi Kenya Department of Statistics and Actuarial Sciences Jomo Kenyatta University of Agriculture and Technology Nairobi Kenya
出 版 物：《Open Journal of Statistics》 (统计学期刊（英文）)
年 卷 期：2022年第12卷第5期
页 面：676-690页
学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学]
主 题：Fuzzy Regression Discontinuity Fuzzification Centroid Method of Defuzzification Membership Function
摘 要：Despite the fact that fuzzy regression discontinuity designs are growing in popularity, a lot of research takes into account treatment non-compliance difficulties, specifically the fuzziness of the treatment impact. This paper took into account independent and dependent fuzzy factors when creating these designs. Additionally we took into account treatment non-compliance difficulties, specifically the fuzziness of the treatment impact, as other research does. The modified Fuzzy Regression Discontinuity model is preferable for modeling fuzzy data. It enables us to draw improved causal effects accommodating fuzzy variables, not just the fuzziness of the treatment effect as in Fuzzy Regression Discontinuity models. A fuzzy dataset is converted into crisp data by the Centroid method of defuzzification. Once the data is crisp, the traditional least squares methods of approximation are used to estimate the parameters in the model since these parameters are considered crisp whilst the error terms are fuzzy. The Alcohol Use Disorders Identification Test score(AUDIT score) can be used as a cutoff to initiate treatment in this case and can be used to predict the progression of HIV disease and/or AIDS. Counseling helps to lower the use of alcohol in people living with HIV/AIDS (PLWHA) as a result, improving the participants’ CD4 counts.
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