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Family structure and child outcomes: an illusive relationship Don Kerr King’s University College PowerPoint Presentation
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Family structure and child outcomes: an illusive relationship Don Kerr King’s University College

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Family structure and child outcomes: an illusive relationship Don Kerr King’s University College

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  1. Family structure and child outcomes: an illusive relationship Don Kerr King’s University College University of Western Ontario 2004 Canadian Population Society Meetings Winnipeg, Manitoba

  2. To what extent is"family structure” important in predictingchild outcomes? • 2 issues: • Why should “family structure matter”? • What empirical evidence is currently available on this issue with the NLSCY?

  3. Behavioral Scales for Children 4-11, NLSCY (first cycle) by Family Type

  4. Why should “family structure matter”? • In both step and lone parent families child loses out from the lack of co-residence with one biological parent • -> less parental supervision • -> lower transfer of social & human capital (Amato & Booth, 1997) • There is no consensus on this issue!!!

  5. In working with the first wave of the NLSCY • Multivariate analyses: -> family type is found to be a useful predictor of childhood difficulties • -> association persists with controls for low income, age, educ, etc. • What does this cross sectional association represent??? > the impact of being raised in a lone parent/step family OR > the impact of “antecedent” factors i.e. what lead to the formation of the lone parent/step family in the first place? (conflict, abuse?)

  6. In Longitudinal analysis: • -> most common approach: • “autoregressive or residual change analysis” • -> An alternative is now possible (4 cycles of the NLSCY) • Latent Growth Curve Models (LGM)

  7. Autoregressive or Residual change approach 1994 2000 Child outcome 2000 Child outcome 1994 Family structure, income, etc. • Many critiques of this approach • Rogosa et al. 1982; Rogosa and Willett (1985)

  8. As an alternative: • Latent Growth Curve Models (LGM) • Duncan et al (1999) • -> does not model variance at a specific point in time • -> attempts to model individual trajectories on dependent variable over time

  9. Example: with consistent measures of hyperactivity: over 4 cycles (1994, 1996, 1998, 2000) Score on hyperactivity scale

  10. Latent Growth Models Intercept Slope Scale on externalizing problems 1994 1996 1998 2000 E2 E3 E4 E1

  11. Latent Growth Models Mean -.565* Var .466 Mean 4.9 Var 6.7 Intercept Slope Scale on externalizing problems 1994 1996 1998 2000 E2 E3 E4 E1

  12. Latent Growth Models Lone parent 1994-2000 -.05ns .176* Mean -.565 Var .466 Mean 4.9 Var 6.7 Intercept Slope Scale on externalizing problems 1994 1996 1998 2000 E2 E3 E4 E1

  13. Latent Growth Models Lone parent 1994-2000 Low income 1994-2000 -.05ns -.033ns .176* .099* Mean -.565 Var .466 Mean 4.9 Var 6.7 Intercept Slope Scale on externalizing problems 1994 1996 1998 2000 E2 E3 E4 E1

  14. GFI=.970 CFI=.971 χ2 =355.6 df = 13 Latent Growth Models Lone parent 1994-2000 Step Family 1994-2000 Low income 1994-2000 -.05ns .132* -.033ns .107* .176* .099* Mean -.565 Var .466 Mean 4.9 Var 6.7 Intercept Slope Scale on externalizing problems 1994 1996 1998 2000 E2 E3 E4 E1

  15. Conclusion: • Results are preliminary • Results are very mixed as to the importance of family structure • Future research -> additional controls/behavioral scales • LGM looks particularly promising in the analysis of change