This research was supported by NIMH Grant MH081087 awarded to the first author. This study uses data from Add Health, a program project designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris, and funded by Grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 17 other agencies. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Persons interested in obtaining data files from Add Health should contact Add Health, Carolina Population Center, 123 W. Franklin Street, Chapel Hill, NC 27516–2524 (firstname.lastname@example.org). No direct support was received from Grant P01-HD31921 for this analysis.
School Attendance Problems and Youth Psychopathology: Structural Cross-Lagged Regression Models in Three Longitudinal Data Sets
Version of Record online: 21 DEC 2011
© 2011 The Authors. Child Development © 2011 Society for Research in Child Development, Inc.
Volume 83, Issue 1, pages 351–366, January/February 2012
How to Cite
Wood, J. J., Lynne-Landsman, S. D., Langer, D. A., Wood, P. A., Clark, S. L., Mark Eddy, J. and Ialongo, N. (2012), School Attendance Problems and Youth Psychopathology: Structural Cross-Lagged Regression Models in Three Longitudinal Data Sets. Child Development, 83: 351–366. doi: 10.1111/j.1467-8624.2011.01677.x
- Issue online: 25 JAN 2012
- Version of Record online: 21 DEC 2011
This study tests a model of reciprocal influences between absenteeism and youth psychopathology using 3 longitudinal datasets (Ns = 20,745, 2,311, and 671). Participants in 1st through 12th grades were interviewed annually or biannually. Measures of psychopathology include self-, parent-, and teacher-report questionnaires. Structural cross-lagged regression models were tested. In a nationally representative data set (Add Health), middle school students with relatively greater absenteeism at Study Year 1 tended toward increased depression and conduct problems in Study Year 2, over and above the effects of autoregressive associations and demographic covariates. The opposite direction of effects was found for both middle and high school students. Analyses with 2 regionally representative data sets were also partially supportive. Longitudinal links were more evident in adolescence than in childhood.