Measurement invariance of DSM-IV alcohol, marijuana and cocaine dependence between community-sampled and clinically overselected studies
Article first published online: 7 MAY 2013
© 2013 The Authors, Addiction © 2013 Society for the Study of Addiction
Volume 108, Issue 10, pages 1767–1776, October 2013
How to Cite
Derringer, J., Krueger, R. F., Dick, D. M., Agrawal, A., Bucholz, K. K., Foroud, T., Grucza, R. A., Hesselbrock, M. N., Hesselbrock, V., Kramer, J., Nurnberger, J. I., Schuckit, M., Bierut, L. J., Iacono, W. G. and McGue, M. (2013), Measurement invariance of DSM-IV alcohol, marijuana and cocaine dependence between community-sampled and clinically overselected studies. Addiction, 108: 1767–1776. doi: 10.1111/add.12187
- Issue published online: 13 SEP 2013
- Article first published online: 7 MAY 2013
- Manuscript Accepted: 6 MAR 2013
- Manuscript Revised: 24 AUG 2012
- Manuscript Received: 9 JUL 2012
- NIH. Grant Numbers: DA029377, MH016880, DA23668, DA25886, AA09367, DA05147
- NIH Genes, Environment and Health Initiative [GEI]. Grant Numbers: U01 HG004422, U01HG004438
- GENEVA Coordinating Center. Grant Number: U01 HG004446
- National Institute on Alcohol Abuse and Alcoholism
- National Institute on Drug Abuse
- NIH contract ‘High throughput genotyping for studying the genetic contributions to human disease’. Grant Number: HHSN268200782096C
- Item response theory;
- sampling comparison;
- sex differences;
- substance dependence
To examine whether DSM-IV symptoms of substance dependence are psychometrically equivalent between existing community-sampled and clinically overselected studies.
A total of 2476 adult twins born in Minnesota and 4121 unrelated adult participants from a case–control study of alcohol dependence.
Life-time DSM-IV alcohol, marijuana and cocaine dependence symptoms and ever use of each substance.
We fitted a hierarchical model to the data, in which ever use and dependence symptoms for each substance were indicators of alcohol, marijuana or cocaine dependence which were, in turn, indicators of a multi-substance dependence factor. We then tested the model for measurement invariance across participant groups, defined by study source and participant sex.
The hierarchical model fitted well among males and females within each sample [comparative fit index (CFI) > 0.96, Tucker–Lewis index (TLI) > 0.95 and root mean square error of approximation (RMSEA) < 0.04 for all], and a multi-group model demonstrated that model parameters were equivalent across sample- and sex-defined groups (ΔCFI = 0.002 between constrained and unconstrained models). Differences between groups in symptom endorsement rates could be expressed solely as mean differences in the multi-substance dependence factor.
Life-time substance dependence symptoms fitted a dimensional model well. Although clinically overselected participants endorsed more dependence symptoms, on average, than community-sampled participants, the pattern of symptom endorsement was similar across groups. From a measurement perspective, DSM-IV criteria are equally appropriate for describing substance dependence across different sampling methods.