1. Reunification for Siblings in Out-of-Home Care Using a Statistical Technique for Examining Non-independent Observations Presented by: Joseph Magruder, MSW Center for Social Services Research University of California, Berkeley Paper Authored by: Daniel Webster, PhD Aron Shlonsky, PhD Terry Shaw, MSW M. Alan Brookhart, PhD National Association for Welfare Research and Statistics 45 th Annual Workshop Madison, Wisconsin August 31, 2005 The Performance Indicators Project at CSSR is supported by the California Department of Social Services and the Stuart Foundation

2. Background Increasing use of administrative data, often containing entire populations Evidence that siblings comprise more than half of all children in out-of-home care Sampling bias posed by failing to account for interdependence of siblings

3. Background continued... Little past research has used sibling information in either multivariate or longitudinal analysis Shlonsky, Webster, & Needell (2003) Guo & Wells (2003) Special issue of Children and Youth Services Review (2005) Present study builds on this past work Incorporates method that accounts for non-independence of siblings when using a generalized linear model such as logistic regression Includes sibling constructs as covariates

4. Study Sample California Children’s Services Archive Data System Jan. 1, 2000 – Dec. 31, 2000 Entry Cohort in care 5 days or more into Child Welfare Supervised Care (with at least one sibling who entered care during that time) Primary placements shelter, guardian, missing excluded; final study sample accounted for 56% of all first entries for the calendar year (N=15,517) Children were followed from initial placement for 12 months (or discharge from care if that occurred sooner)

5. Analysis Multivariate model of reunification versus not by 12 months after entry to care Proc GENMOD (using generalized estimating equations--GEE) instead of Proc LOGISTIC Same parameters—larger Standard Errors (wider Confidence Intervals) Requires a clustering variable (e.g., family id) Conventional logit for comparison

6. Results  Estimates for most factors (age, removal reason, placement type, and placement moves) consistent with past reunification studies  Strong relationship between sibling group covariates and likelihood of reunification: - Sibs placed initially with at least one other sibling in same home had about one third greater odds of reunifying (OR=1.30) than sibs not placed together - Sibs placed initially all together in same home had almost twice the odds of reunifying (OR=1.82) - Surprisingly, large sibling groups (6 or more children) no less likely to reunify  Estimates from conventional logit run as comparison demonstrate need to control for autocorrelation - Some categories change from significant to highly significant, or non- significant to significant

7. CORRECTED (GEE) estimate Three Siblings = 0.00995 odds ratio = 1.01 SE= 0.071 95% CI = (0.88, 1.16) UNCORRECTED (Logit) estimate Three Siblings = 0.00995 odds ratio = 1.01 SE= 0.047 95% CI = (0.92, 1.11) Lack of correction may over-assign “statistical significance”, etc. Model Estimates Example

8. CORRECTED (GEE) estimate Six Siblings = -.2006 odds ratio = 0.82 SE= 0.214 95% CI = (0.54, 1.24) UNCORRECTED (Logit) estimate Six Siblings = -.2006 odds ratio = 0.82 SE= 0.119 95% CI = (0.61, 0.96) Lack of correction may mis-assign “statistical significance”, etc. Model Estimates Example

9. Odd Ratios from GEE and Comparison Logit GEE Logit Two 1.001.00 Three 1.01 1.01 Four 1.06 1.06 Five 1.071.07 Six 0.82 ns 0.82* Seven or more 0.82 ns 0.82* ns Not significant * Statistically significant ** Highly statistically significant Number of Siblings in Group GEE Logit Not together 1.001.00 All placed together1.82**1.82** Some placed together 1.30*1.30** Siblings Placed Together in First Placement

10. Odd Ratios from GEE and Comparison Logit Ethnic Group GEE Logit White 1.001.00 Black 0.96 0.96 Hispanic 0.81** 0.81** Asian/PI 1.56* 1.56** Native Amer. 0.58* 0.58** * Statistically significant ** Highly statistically significant

11. Discussion Limitations of present study  Shortcomings of administrative data  Single entry cohort for one calendar year  Children continue to reunify after twelve months Incorporating sibling-specific information gives new insights to longitudinal outcomes such as reunification When using logistic regression, issues about statistical significance due to lack of independence can be corrected using Proc Genmod (GEE) in SAS

12. Comments, Questions, or Reprints Please Contact: Daniel Webster, PhD Center for Social Services Research School of Social Welfare 16 Haviland Hall University of California Berkeley, CA 94720 510.290.6779 dwebster@berkeley.edu Paper citation: Webster, D., Shlonsky, A., Shaw, T., & Brookhart, A. (2005). The ties that bind II: Reunification for siblings in out-of-home care using a statistical technique for examining non-independent observations. Children and Youth Services Review, 27(7), 765-782.