@article{ref1,
title="Marginal structural models for estimating the longitudinal effects of community violence exposure on youths' internalizing and externalizing symptoms",
journal="Psychological trauma: theory, research, practice, and policy",
year="2022",
author="Kennedy, Traci M. and Kennedy, Edward H. and Ceballo, Rosario",
volume="ePub",
number="ePub",
pages="ePub-ePub",
abstract="OBJECTIVE: Longitudinal observational data pose a challenge for causal inference when the exposure of interest varies over time alongside time-dependent confounders, which often occurs in trauma research. We describe marginal structural models (MSMs) using inverse probability weighting as a useful solution under several assumptions that are well-suited to estimating causal effects in trauma research. <br><br>METHOD: We illustrate the application of MSMs by estimating the joint effects of community violence exposure across time on youths' internalizing and externalizing symptoms. Our sample included 4,327 youth (50% female, 50% male; 1.4% Asian American or Pacific Islander, 34.7% Black, 46.9% Hispanic,.8% Native American, 14.3%, White, 1.5%, Other race/ethnicity; M(age) at baseline = 8.62, range = 3-15) from the Project on Human Development in Chicago Neighborhoods. <br><br>RESULTS: Wave 3 internalizing symptoms increased linearly with increases in Wave 2 and Wave 3 community violence exposure, whereas effects on externalizing symptoms were quadratic for Wave 2 community violence exposure and linear for Wave 3. These results fail to provide support for the desensitization model of community violence exposure. <br><br>CONCLUSION: MSMs are a useful tool for researchers who rely on longitudinal observational data to estimate causal effects of time-varying exposures, as is often the case in the study of psychological trauma. (PsycInfo Database Record (c) 2022 APA, all rights reserved).<p /> <p>Language: en</p>",
language="en",
issn="1942-9681",
doi="10.1037/tra0001398",
url="http://dx.doi.org/10.1037/tra0001398"
}