Fuzzy Set Theory: Applications in the Social Sciences, Issue 147This book introduces fuzzy set theory to social science researchers. Fuzzy sets are categories with blurred boundaries. With classical sets, objects are either in the set or not, but objects can belong partially to more than one fuzzy set at a time. Many concepts in the social sciences have this characteristic, and fuzzy set theory provides methods for systematically dealing with them. A primary reason for not going beyond programmatic statements and rather unsophisticated uses of fuzzy set theory has been the lack of practical methods for combining fuzzy set concepts with statistical methods. This monograph takes that topic as its major focus, and provides explicit guides for researchers who would like to harness fuzzy set concepts while being able to make statistical inferences and test their models. Real examples and data-sets from several disciplines illustrate the techniques and applications, demonstrating how a combination of fuzzy sets and statistics enable researchers to analyze their data in new ways. |
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Aggres Anx./Dep anxiety/depression applications assess Avoid 0 ms(2 bership beta distribution bivariate cell censored Chapter chi-square citrus clinical co-occurrence comorbidity rates components conditional membership confidence interval correlations covariance crisp sets cutoff defined degree of membership Delinq Democracy Index diagonal path Dislike distribution endpoints error bands example focal set full membership fuzzy inclusion fuzzy intersection fuzzy set approach fuzzy set concepts fuzzy set theory inclusion coefficients inclusion rate intermediate membership intersections and unions JCDF joint ordering linear filter logistic regression m₁(x mathematical mean membership measure of fuzziness membership assignments membership function membership scale membership values multiple multiset nonmembership Nonreferred and Referred nonreferred sample product operator proportion raw comorbidities referred sample sample compared scalar cardinality scatterplots scores Seek Not Avoid set-theoretic seven-syndrome single-syndrome Smithson social sciences Somatic standard statistically independent Table techniques thought disorder tobit model Torino Scale unit interval variables Verkuilen
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Page 90 - Inverses of fuzzy relations: Applications to possibility distributions and medical diagnosis.
Page 87 - Broughton, R. (1984). A prototype strategy for construction of personality scales. Journal of Personality and Social Psychology, 47, 1334-1346. Broughton, R. (1990). The prototype concept in personality assessment. Canadian Psychology, 31, 26-37. Burisch, M. (1984). Approaches to personality inventory construction: A comparison of merits. American Psychologist, 39, 214-227.