1. Beyond Indices? The potential of fuzzy set ideal type analysis for comparative analysis of children’s well being John Hudson and Stefan Kühner Department of Social Policy & Social Work, University of York, UK

2. Overview Methodological paper Replication of UNICEF Innocenti Report Card 7 Utilising Fuzzy Set Ideal Type Analysis Test potential of non-linear methods

3. UNICEF Study

4. Problems with Indices? Compensation effects? Antithetical components? Outliers and extreme cases?

5. Fuzzy Set Ideal Type Analysis Membership, non-membership Calibration Boolean algebra: –NOT (negation principle) –AND (minimum principle) Venn diagram AbaBAB ab

6. Outliers and influential cases

7. Antithetical Components

8. Fuzzy Set Calibration

9. Dimension Reduction:(1) Simple OLS Regression/ Cook’s D (2) Bivariate correlation/principle components analysis (3) Objective knowledge Fuzzy Set Calibration:(1)Box-plot/outliers/extreme cases (2) Adjusted means and standard deviations Fuzzy Set Ideal Type Analysis

10. MaterialEducationFamilySubjective Well Being Behaviour and Lifestyles AffluenceAttainment AND Inclusion Structures OR Relationships Life Attitude AND Belonging Risk AND Health 19 Indicators 4 of 54 of 64 of 54 of 63 of 12 Health / safety: 0 of 6

11. Aut, Ger Cze Gre, Pol Den Fin Ire Swe, Net Hun, UK Net Subjective Material Education Relationships Behaviour Por  

12. Conclusions Complexity/lack of familiarity a disadvantage Ideal types allow simple: –Identification of exemplar –Identification of areas of weaknesses in each case Also: –Copes better with diversity (e.g. family) –Mitigates impact of outliers on findings At very least: worthy of further exploration