Citation

Schmidt LA, Tam TW, Larson MJ. J. Stud. Alcohol Drugs 2012; 73(1): 144-153.

Affiliation

Philip R. Lee Institute for Health Policy Studies and Department of Anthropology, History and Social Medicine, University of California, San Francisco, San Francisco, California.

Copyright

(Copyright © 2012, Alcohol Research Documentation, Inc., Rutgers, The State University of New Jersey)

DOI

unavailable

PMID

22152672

PMCID

PMC3237705

Abstract

Objective: This study examined the potential for biased inference due to endogeneity when using standard approaches for modeling the utilization of alcohol and drug treatment. Method: Results from standard regression analysis were compared with those that controlled for endogeneity using instrumental variables estimation. Comparable models predicted the likelihood of receiving alcohol treatment based on the widely used Aday and Andersen medical care-seeking model. Data were from the National Epidemiologic Survey on Alcohol and Related Conditions and included a representative sample of adults in households and group quarters throughout the contiguous United States. Results: Findings suggested that standard approaches for modeling treatment utilization are prone to bias because of uncontrolled reverse causation and omitted variables. Compared with instrumental variables estimation, standard regression analyses produced downwardly biased estimates of the impact of alcohol problem severity on the likelihood of receiving care. Conclusions: Standard approaches for modeling service utilization are prone to underestimating the true effects of problem severity on service use. Biased inference could lead to inaccurate policy recommendations, for example, by suggesting that people with milder forms of substance use disorder are more likely to receive care than is actually the case. (J. Stud. Alcohol Drugs, 73, 144-153, 2012).

Language: en