Estimating sibling spillover effects with unobserved confounding using gain-scores
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Updated: Oct 7, 2025

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
Published on: September 17, 2019
David C Mallinson1, Felix Elwert2
1Population Research Center, University of Texas, Austin, TX.
Purpose:
A growing area of research in epidemiology is the identification of health-related sibling spillover effects, or the effect of one individual's exposure on their sibling's outcome. The health within families may be confounded by unobserved factors, rendering identification of sibling spillovers challenging.
Methods:
We demonstrate a gain-score (fixed effects) regression method for identifying exposure-to-outcome spillover effects within sibling pairs in linear models. The method identifies the exposure-to-outcome spillover effect if only one sibling's exposure affects the other's outcome, and it identifies the difference between the spillover effects if both siblings' exposures affect the others' outcomes. The method fails with outcome-to-exposure spillover or with outcome-to-outcome spillover. Analytic results, Monte Carlo simulations, and a brief application demonstrate the method and its limitations.
Results:
We estimate the spillover effect of a child's preterm birth on an older sibling's literacy skills, measured by the Phonological Awareness Literacy Screening-Kindergarten test. We analyze 20,010 sibling pairs from a population-wide, Wisconsin-based (United States) birth cohort. Without covariate adjustment, we estimate that preterm birth modestly decreases an older sibling's test score.
Conclusions:
Gain-scores are a promising strategy for identifying exposure-to-outcome spillover effects in sibling pairs while controlling for sibling-invariant unobserved confounding.
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