Fuzzy Least Squares Regression Analysis for Social Judgment Study
Department of Psychology, Waseda University, 1-24-1 Toyama, Shinjuku-Ku, Tokyo 162-8644, Japan
Social judgment data was analyzed using fuzzy least squares regression analysis based on the extension principle. The proposed analysis is new fuzzy least squares regression analysis in which input data, output data, and coefficients are represented by L-R fuzzy numbers. To evaluate data fitness, we propose a fuzzy version of a squared multiple correlation (R2) and conducted an experiment to determine the effect of partial attribute information on the overall evaluation of desirability for a marital partner and personality of a person using fuzzy rating to measure vagueness in social judgment. Participants in the experiment were 90 university students. The result of marital partner judgment indicated that the fuzzy weight of consideration was higher than physical attraction on overall desirability evaluation for a marriage partner. The result of personality judgment indicated that the fuzzy weight of kindness was slightly higher than responsibility in overall desirability for a marriage candidate.