DEVELOPMENTS IN CROSS-NATIONAL RESEARCH

1. DEVELOPMENTS IN CROSS-NATIONAL RESEARCH Jacques A. Hagenaars Department of Methodology, Faculty of Social Sciences, Tilburg University QMSS Conference 2007, Prague, 20-23 June 2007

2. CROSS-NATIONAL RESEARCH MODES Varieties • Single case/nation study: process analyses, and use of counterfactuals, ruling out confounding factors • comparisons of a few strategic cases: process analyses, counterfactuals, comparative logic • Many cases/nations at the macro level: QCA and quantitative macro analyses • Several cases/nations studied at the individual level, contextual analyses Purpose • Generalization versusquasi-experimental design

3. MAIN DEVELOPMENTS ‘quantitative’, cross-national large scale surveys • Operationalization, fieldwork • analysis: multilevel models, measurement models ‘qualitative’ comparative research, comparative case studies • Boolean algebra (crisp sets, QCA) • fuzzy sets (QCA) • polytomies (MVQCA)

4. OLDPROBLEMS (thatremain) Comparability • Concepts: depending on • Nature of concept: universals or culturally determined particulars; nominalism, operationalism, realism, essentialism • Cultural distance • Operationalizations: indicators, questions, translation, sampling, interviewing modes etc, etc. • Identical versus equivalent

5. OLD PROBLEMS (continued) Selection of cases • which cases: convenience or strategic: • Mill’s Method of Agreement (eliminating necessary causes) • Mill’s Method of difference (eliminating sufficient causes) • MSDO/ MDSO(/MSSO), MSSD/MDSD: selection on independent and/or dependent variables • Generalizibility: theoretical versus operational universe • Confounding factors • Lack of variation/multicollinearity

6. ADVANCEMENTS IN QUANTITATIVE CROSS-NATIONAL RESEARCH Operationalization • Availability of Data • Standardized and controlled operationalization and field procedures • Random sampling is practically possible • Translation • Backward translation • TRAPD: Translation, Review, Adjudication, Pre-testing and Documentation

7. ADVANCEMENTS IN QUANTITATIVE CROSS-NATIONAL RESEARCH (cont) Analysis: multilevel models • Connecting statements about macro-level, micro-level, and cross-level relationships, e.g., • One-step or two-step estimation • Random or fixed???

8. ADVANCEMENTS IN QUANTITATIVE CROSS-NATIONAL RESEARCH (cont) Analysis: comparative measurement models • Latent structure models; item bias; dif a) C X b) C X c) C X A B A B A B C-Country; X-latent; A, B-indicators n.b identity or equivalence!

9. Analysis: comparative measurement models (cont) • MTMM-experiments (Multi-Trait Multi-Methods) F1 F2 M T1 T2 e1 Y1 Y2 e2

10. Analysis: comparative measurement models (cont) • Latent structure models: factor analysis, latent class, latent trait models, etc • LCA

11. Analysis: comparative measurement models (cont) • Skewed distributions • Unequal intervals/Nonlinear relationships (nominal, ordinal, interval levels for both latent and manifest variables)

12. Analysis: comparative measurement models (cont) • EVS 1999; comparative interval/nominal LCA analysis How often attend religious ceremonies: 1. More than once a week; 2.once a week; 3.once a month; 4. Christmas/Eastern; 5.Other special holy days;6.once a year; 7.less often; 8.(practically) never • Country homogenous model: different intervals: -13.6 -4.6 .4 1.5 2.5 3.4 4.7 5.7 • Country by country: different intervals in different countries, even reversals of category order • In Turkey: scores for Men different from Women’s scores

13. ADVANCEMENTS IN QUALITATIVE CROSS-NATIONAL RESEARCH • QCA: qualitative comparative analysis • Take a number of cases (>10) • Assign cases to having experienced the (dependent) event or not: R/r (to belonging to cat. 1 or 2 of the dependent variable); assign cases in a similar way to the dichotomous categories of the independent variables • Formulate the outcomes in terms of ‘Boolean algebra’, truth tables, set theory, with Union/or: A+b+c intersection/and: Abc

14. ADVANCEMENTS IN QUALITATIVE CROSS-NATIONAL RESEARCH (continued) • R = Abc + aBc + abC + ABc + AbC +aBC + ABC • Boolean minimization, e.g, Ab + AB = A(b+B)=A, in the end: R = A + B + C • Interpretation in terms of necessary and sufficient conditions • Extensions to polytomies • Extension to fuzzy sets • MARVELOUS WAY OF FORMALIZING THE LOGIC OF COMPARATIVE ANALYSES

15. ADVANCEMENTS IN QUALITATIVE CROSS-NATIONAL RESEARCH (continued) • Limitations • No process analysis, no causal chains • Only case level analysis • Fuzzy set: no good procedures for assigning probabilities, but outcomes may heavily depend on it.

16. ADVANCEMENTS IN QUALITATIVE CROSS-NATIONAL RESEARCH (continued) Methodological objections (against underlying methodology (ideology)): • Configurational complexity is not a virtue! • Why then Boolean minimization? • The world is complex, but our explanations should be as parsimonious as possible (falisfiability/more information/exclude more states of the world); cf also chaos theory, permutations etc. • Often caused by extreme multicollinearity • Fuzzy sets: chance, error has no place in case studies (cf KKV)

17. Did we make progress? OF COURSE!

18. Did we make progress? OF COURSE! Will you make progress? OF COURSE

19. Did we make progress? OF COURSE! Will you make progress? OF COURSE Will all problems ever be solved? OF COURSE NOT!