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Maarten L. Buis & Harry B.G. Ganzeboom Department of Social Research Methodology

Trends in Inequality of Educational Opportunity in the Netherlands 1900-1980: The Effect of Missing Data. Maarten L. Buis & Harry B.G. Ganzeboom Department of Social Research Methodology Vrije Universiteit Amsterdam RC28, Oslo, May 6-8 2005. Conclusions (1).

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Maarten L. Buis & Harry B.G. Ganzeboom Department of Social Research Methodology

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  1. Trends in Inequality of Educational Opportunity in the Netherlands 1900-1980:The Effect of Missing Data Maarten L. Buis & Harry B.G. Ganzeboom Department of Social Research Methodology Vrije Universiteit Amsterdam RC28, Oslo, May 6-8 2005

  2. Conclusions (1) • A steady trend towards less IEO in the Netherlands remains visible throughout the 20th century. • However, on closer scrutiny there appears to be evidence of a slower trend or even stability for the earlier and most recent cohorts. • Spline analyses of trends confirms this. Buis & Ganzeboom, Oslo 2005

  3. Conclusions (2) • Missing data in father’s occupation vary by education of respondent: MV are about 3 times more prevalent among the lowest educated than among the highest educated. • One would hypothesize that this mitigates measures of IEO and the historical trend therein. • Multiply imputed data for FISEI: • Level of IEO increases • (Linear) trends in IEO becomes steeper Buis & Ganzeboom, Oslo 2005

  4. Previous research • IEO = Inequality of Educational Opportunity = association between father’s occupation and respondent’s education. • Previous research: long-term linear trend towards less IEO: • Cohorts 1900-1960: Ganzeboom & De Graaf, 1989, De Graaf & Ganzeboom, 1990a, 1990b. • Cohorts 1900-1980: Ganzeboom & Luijkx, 2004. • This holds for both linear regression models en sequential logits (first two transitions). Buis & Ganzeboom, Oslo 2005

  5. ISMF • Now 51 studies on the Netherlands, collected between 1958 and 2004, N > 104.000 men and women 25+. • Recent additions (since 2002 and Breen 2004): 16 studies, appr. 30% of the N. • Father: FISEI – International Socio-economic Index of Occupational Status. • Education: level of education scaled relative to benchmarks: primary = 6, highest secondary = 12, university complete = 17. Buis & Ganzeboom, Oslo 2005

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  7. Research questions • How do trend and level estimates of IEO depend upon data qualities: • Measures used • Quality and nature of the sample • Non-response • Missing values Buis & Ganzeboom, Oslo 2005

  8. Missing values • MCAR = Missing Completely at Random • MAR = Missing at Random: missingness is random given the values of control (X) variables. • NMAR: Not Missing at Random: missingness depends upon values of Y-variable. • Rubin 1987, Little & Rubin 2002, Allison 2002. • Multiple hotdeck imputation in STATA. Buis & Ganzeboom, Oslo 2005

  9. Complete case analysis(listwise deletion) • OK, if MCAR. • Biased if MAR. • Inefficient (too large standard errors – this can be quite dramatic. • Linear trend: • EDU = 8.4 + 6.4*FIS – 5.3*FIS*COH etc. (Men) (.17) (.08) (.45) • EDU = 6.5 + 5.6*FIS – 3.3*FIS*COH etc. (Women) (.17) (.08) (.44) Buis & Ganzeboom, Oslo 2005

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  11. Hot deck imputation • Classify all cases by combinations of predictor variables (COH, FED, MED, ISEI). • Stratify the cases by these combinations. • Substitute the missing FISEI by valid FISEI of random (nearest) neighbor. • Key idea: do not only borrow the systematic (predicted) part, but also the error term. Buis & Ganzeboom, Oslo 2005

  12. Multiple hot deck imputation • Do hot deck imputation several times (10-20). • Bootstrap from each stratum a sample (with replacement) of stratum size. • Random selection of neighbor varies by imputation cycle. • Key idea: Rubin (1987): pp. 122-124. Get the variance-covariance estimation right. Buis & Ganzeboom, Oslo 2005

  13. Key results • FISEI predicted by COH (4), FED (7), MED (7), ISEI (8). • 10 imputations • Linear trend result: • EDU = 8.6 + 6.9*FIS – 6.1*FIS*COH etc. (Men) (.33) (.12) (.64) • EDU = 6.7 + 5.9*FIS – 3.7*FIS*COH etc. (Women) (.46) (.12) (.64) Buis & Ganzeboom, Oslo 2005

  14. Non-linearities • Linear splines • Estimates with 1, 2, 3, 4 etc. knots (and a uniform distribution). We were happy with the result with 3 knots. • Test of equality of slopes: • Between trajectories • Between men and women Buis & Ganzeboom, Oslo 2005

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  16. Results • Complete case analysis finds: • Decline in IEO occurs between cohorts 1920 and 1960. Before 1920 and after 1960, the trend can be assumed to be flat. • There is a constant difference in IEO between men and women: women’s educational attainment appr. 10% less dependent on FIS than men’s. Buis & Ganzeboom, Oslo 2005

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  18. Multiple hot deck imputed data • Finds pattern very similar to complete case analysis. • But decline of IEO between 1920 and 1960 is steeper! • However, standard errors of effects have increased (despite inclusion of more information). Buis & Ganzeboom, Oslo 2005

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