Rob French

1. Exploring the role of the family in multilevel models of school effectiveness and student achievement using Swedish registry data Rob French Longitudinal data analysis: Methods & Applications6th ESRC Research Methods Festival11:15 Wed 9th July 2014

2. School effectiveness • Pupils in schools: (Raudenbush & Bryk, 1986); (Aitkin & Longford, 1986) (Goldstein et al., 1993)

3. Goldstein, 2011 ‘Multilevel Statistical Models’

4. Families & achievement • Are families important for school effectiveness studies? • Pupils in families: (Jenkins et al., 2005) (Georgiades et al., 2008) • Pupils in schools & families: (Rasbash et al., 2010)

5. Rasbash et al. (2010)

6. Rasbash et al. (2010)

7. Family structure • Birth order (Belmont & Marolla 1973), within family (Rodgers et al. 2000), (Wichman et al. 2006) • Family size (Hanushek 1992), (Blake 1981), (Conger et al. 2000), (Kuo & Hauser 1997), (Iacovou 2008) • Family Spacing (Zajonc 1976) (van Eijsden et al. 2008) • Family sibling sex composition (Bound et al. 1986), (Butcher & Case 1994), (Hauser & Kuo 1998), (Powell & Steelman 1989)

8. Research Questions • How much of the within school variation in achievement in school effectiveness models should be attributed to the family? • Which family structure characteristics are important for explaining differences in achievement between students and families?

9. Data • Swedish pupil registry datasets • 4 cohorts (students who finish compulsory schooling in 2006, 2007, 2008 & 2009) • 339,897 pupils in analysis, 1,295 schools, 5,341 neighbourhoods and 288,974 families • Outcome measure = student achievement sum of score (0,10,15 or 20) across 16 subjects - standardised for analysis

10. Defining family & family structure variables • We have 2 ways of identifying families: • Genetic relatedness • Mother ID & father ID • We define the family as children with common mothers and fathers (+ other possible definitions…) • Problems: • Family is constructed only for individuals in the 4 cohorts of data and ignores siblings from earlier / later cohorts • Family structure variables are also constructed only from the 4 cohorts of data.

11. Independent variables Family structure: • Birth order: categorical variable (1st born is reference). • Family size: categorical variable (1 child family is reference). • Family Spacing: age gap between oldest and youngest recoded as categorical variable: 0 spacing (reference), 1-24 months, 25-48 months. • Family sibling sex composition: mixed sex sibships vs. single sex sibships. Other variables: gender, immigration status, age within year

12. Twins: Model A: Pupils in schools All siblings: , , School Pupil • Model of student achievement of pupil i nested in school j • Twins approach uses dummy variable for twin children • Siblings approach uses cohort dummies

13. Model B: Pupils in families Families Pupil • Model of student achievement of pupil i nested in family j • Twins approach uses the twin dummy variable to switch between twin families (1% of sample) and singletons

14. Model C & D: Schools + families School Neighbourhood Family Pupil • Model includes school AND family random effects • We also include neighbourhood effects

15. Model A: Pupils in schools • Omitting prior attainment increases the school effects / school variance partition coefficient (VPC) • School effects are much lower for Sweden than England • Using all 4 cohorts makes no difference to school effects for Sweden

16. Model B: Pupils in families • Omitting prior attainment increases the family VPC • Family VPC similar for Sweden and England • Using all 4 cohorts (families now include siblings rather than just twins) reduces family VPC

17. Model C – Schools & families The proportion of variation identified as within school variation that should be attributed to families is 64% in England and 66% in Sweden (using the twins methodology with no prior attainment) This is reduced to 44% when we consider families of siblings rather than simply twins

18. Model D: Age & gender Estimates for ‘Age within year’ similar for England and Sweden Greater gender differences in Sweden

19. Model D: Family structure

20. Family structure: 2 child family Predicted achievement for children from a 2 child family, where both children are girls: • 1st born children have higher predicted achievement than 2nd born • Wider spacing reduces the gap between siblings

21. Family structure: 3 child family Predicted achievement for children from a 3 child family, where all children are girls: • 1st born children have higher predicted achievement than 2ndborn • 2nd born children have higher predicted achievement than 3rd born • Wider spacing reduces the gap between siblings

22. RQ1 - Conclusions • How much of the “within school variation” in school effectiveness models is actually attributable to the family? • We estimate 44% of the within school variation in our school effectiveness model is actually attributable to the family.

23. RQ2 - Conclusions • Which family structure characteristics are important for explaining differences in achievement between students and families? • Birth order has a large negative impact on achievement (interpreted alongside family size) • Wider spacing is associated with higher achievement • Sex composition has no significant association

24. Further work • Additional waves of data to address the problem of family and family structure being defined by families over 4 waves • Identify the genetic component of achievement

25. Literature Belmont, L., Marolla, F.A.: Birth Order, Family Size, and Intelligence A study of a total population of 19-year-old men born in the Netherlands is presented. Science 182(4117), 1096-1101 (1973) Blake, J.: Family Size and the Quality of Children. Demography 18(4), 421-442 (1981) Bound, J., Griliches, Z., Hall, B.H.: Wages, Schooling, and IQ of Brothers and Sisters: Do the Family Factors Differ? National Bureau of Economic Research, (1986) Butcher, K.F., Case, A.: The effect of sibling sex composition on women's education and earnings. The Quarterly Journal of Economics 109(3), 531-563 (1994) Conger, K.J., Rueter, M.A., Conger, R.D.: The role of economic pressure in the lives of parents and their adolescents: The Family Stress Model. (2000) Hanushek, E.A.: The Trade-Off between Child Quantity and Quality. The Journal of Political Economy 100(1), 84-117 (1992) Hauser, R.M., Kuo, H.-H.D.: Does the gender composition of sibships affect women's educational attainment? Journal of Human Resources 33(3) (1998) Iacovou, M.: Family size, birth order, and educational attainment. Marriage & Family Review 42(3), 35-57 (2008) Kuo, H.-H.D., Hauser, R.M.: How does size of sibship matter? Family configuration and family effects on educational attainment. Social Science Research 26(1), 69-94 (1997) Powell, B., Steelman, L.C.: The liability of having brothers: Paying for college and the sex composition of the family. Sociology of Education, 134-147 (1989) Rodgers, J.L., Cleveland, H.H., van den Oord, E., Rowe, D.C.: Resolving the debate over birth order, family size, and intelligence. American Psychologist 55(6), 599 (2000) van Eijsden, M., Smits, L.J., van der Wal, M.F., Bonsel, G.J.: Association between short inter-pregnancy intervals and term birth weight: the role of folate depletion. The American journal of clinical nutrition 88(1), 147-153 (2008) Wichman, A.L., Rodgers, J.L., MacCallum, R.C.: A multilevel approach to the relationship between birth order and intelligence. Personality and social psychology bulletin 32(1), 117-127 (2006) Zajonc, R.B.: Family configuration and intelligence: Variations in scholastic aptitude scores parallel trends in family size and the spacing of children. Science (1976)