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Fuzzy Mediation Analysis

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Abstract

A mediator variable is a variable that causes mediation in the dependent and the independent variables. The mediator variables play important roles in data analysis which involve several variables, especially when the dependent and independent variables are affected by other variables. Thus, mediation analysis is needed in almost all areas that need regression analysis especially in psychology, business, education, science, engineering area, etc. Mediation analysis has been proposed in many studies. However, sometimes it is much more reasonable to express the data using fuzzy theory when the variables are not clearly defined. For example, it is better to express the mood of a person “bad”, “moderate”, “good” using fuzzy numbers than using real numbers (crisp numbers). In this paper, several fuzzy mediation analysis models have been proposed. And confidence intervals and hypothesis tests are also provided. Several psychological data have been applied to find the total, direct and indirect effect when the mediator and confounding variable exist.

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Acknowledgements

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A1B03034813).

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  1. School of Mathematics and Statistics, Sejong University, Seoul, South Korea

    Jin Hee Yoon

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  1. Jin Hee Yoon
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Correspondence to Jin Hee Yoon.

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Yoon, J.H. Fuzzy Mediation Analysis. Int. J. Fuzzy Syst. 22, 338–349 (2020). https://doi.org/10.1007/s40815-019-00727-6

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  • DOI: https://doi.org/10.1007/s40815-019-00727-6

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