The complexity of school and neighbourhood effects and movements of pupils on school differences in models of educational achievement

Traditional studies of school differences in educational achievement use multilevel modelling techniques to take into account the nesting of pupils within schools. However, educational data are known to have more complex non-hierarchical structures. The potential importance of such structures is apparent when considering the effect of pupil mobility during secondary schooling on educational achievement. Movements of pupils between schools suggest that we should model pupils as belonging to the series of schools that are attended and not just their final school. Since these school moves are strongly linked to residential moves, it is important to explore additionally whether achievement is also affected by the history of neighbourhoods that are lived in. Using the national pupil database, this paper combines multiple membership and cross-classified multilevel models to explore simultaneously the relationships between secondary school, primary school, neighbourhood and educational achievement. The results show a negative relationship between pupil mobility and achievement, the strength of which depends greatly on the nature and timing of these moves. Accounting for pupil mobility also reveals that schools and neighbourhoods are more important than shown by previous analysis. A strong primary school effect appears to last long after a child has left that phase of schooling. The additional effect of neighbourhoods, in contrast, is small. Crucially, the rank order of school effects across all types of pupil is sensitive to whether we account for the complexity of the multilevel data structure. Copyright (c) 2009 Royal Statistical Society.

[1]  William J. Browne,et al.  Non-Hierarchical Multilevel Models , 2008 .

[2]  Harvey Goldstein,et al.  Multiple membership multiple classification (MMMC) models , 2001 .

[3]  Stephen W. Raudenbush,et al.  A Crossed Random Effects Model for Unbalanced Data With Applications in Cross-Sectional and Longitudinal Research , 1993 .

[4]  Harvey Goldstein,et al.  The Influence of Secondary and Junior Schools on Sixteen Year Examination Performance: A Cross‐classified Multilevel Analysis∗ , 1997 .

[5]  H. Goldstein,et al.  The use of value added information in judging school performance , 2000 .

[6]  Harvey Goldstein,et al.  Handbook of multilevel analysis , 2008 .

[7]  Harvey Goldstein,et al.  The use of assessment data for school improvement purposes , 1999 .

[8]  M. Aitkin,et al.  Statistical Modelling Issues in School Effectiveness Studies , 1986 .

[9]  William J. Browne,et al.  MCMC Estimation in MlwiN , 2002 .

[10]  Antony Fielding,et al.  Generalized linear mixed models for ordered responses in complex multilevel structures: effects beneath the school or college in education , 2005 .

[11]  H. Goldstein Multilevel mixed linear model analysis using iterative generalized least squares , 1986 .

[12]  Anthony S. Bryk,et al.  Hierarchical Linear Models: Applications and Data Analysis Methods , 1992 .

[13]  Harvey Goldstein,et al.  Partitioning variation in multilevel models , 2002 .

[14]  Harvey Goldstein,et al.  Cross-classified and multiple membership structures in multilevel models : an introduction and review , 2006 .

[15]  Antony Fielding,et al.  Teaching Groups as Foci for Evaluating Performance in Cost-Effectiveness of GCE Advanced Level Provision: Some Practical Methodological Innovations1 , 2002 .

[16]  H. Pan,et al.  A Multilevel Analysis of School Examination Results , 1993 .

[17]  Harvey Goldstein,et al.  Multilevel modelling of health statistics , 2001 .

[18]  William J. Browne,et al.  Modelling non-hierarchical structures , 2001 .

[20]  Anthony S. Bryk,et al.  A Hierarchical Model for Studying School Effects , 1986 .

[21]  Sreenivasan Ravi,et al.  Multilevel Statistical Models, 3rd edn , 2005 .

[22]  H. Goldstein,et al.  Efficient Analysis of Mixed Hierarchical and Cross-Classified Random Structures Using a Multilevel Model , 1994 .

[23]  Harvey Goldstein,et al.  League Tables and Their Limitations: Statistical Issues in Comparisons of Institutional Performance , 1996 .

[24]  Bradley P. Carlin,et al.  Bayesian measures of model complexity and fit , 2002 .

[25]  H. Goldstein Multilevel Statistical Models , 2006 .

[26]  Stephen W. Raudenbush,et al.  Neighborhood Effects on Educational Attainment: A Multilevel Analysis. , 1991 .

[27]  Harvey Goldstein,et al.  Modelling the effect of pupil mobility on school differences in educational achievement , 2007 .