title: Missing data in substance abuse treatment research: current methods and modern approaches.
abstract: Two common procedures for the treatment of missing information, listwise deletion and positive urine analysis (UA) imputation (e.g., if the participant fails to provide urine for analysis, then score the UA positive), may result in significant biases during the interpretation of treatment effects. To compare these approaches and to offer a possible alternative, these two procedures were compared to the multiple imputation (MI) procedure with publicly available data from a recent clinical trial. Listwise deletion, single imputation (i.e., positive UA imputation), and MI missing data procedures were used to comparatively examine the effect of two different buprenorphine/naloxone tapering schedules (7- or 28-days) for opioid addiction on the likelihood of a positive UA (Clinical Trial Network 0003; Ling et al., 2009). The listwise deletion of missing data resulted in a nonsignificant effect for the taper while the positive UA imputation procedure resulted in a significant effect, replicating the original findings by Ling et al. (2009). Although the MI procedure also resulted in a significant effect, the effect size was meaningfully smaller and the standard errors meaningfully larger when compared to the positive UA procedure. This study demonstrates that the researcher can obtain markedly different results depending on how the missing data are handled. Missing data theory suggests that listwise deletion and single imputation procedures should not be used to account for missing information, and that MI has advantages with respect to internal and external validity when the assumption of missing at random can be reasonably supported.
authors.affiliation: College of Nursing, Department of Psychology, Washington State University, Spokane, WA 99210-1295, USA. smcpherson05@wsu.edu
authors.forename: Sterling
authors.initials: S
authors.lastname: McPherson
authors.forename: Celestina
authors.initials: C
authors.lastname: Barbosa-Leiker
authors.forename: G Leonard
authors.initials: GL
authors.lastname: Burns
authors.forename: Donelle
authors.initials: D
authors.lastname: Howell
authors.forename: John
authors.initials: J
authors.lastname: Roll
mesh_terms: D003625:Data Collection / Q000379:methods*; D003627:Data Interpretation, Statistical; D006801:Humans; D016015:Logistic Models; D016032:Randomized Controlled Trials as Topic / Q000379:methods* / Q000706:statistics & numerical data; D019966:Substance-Related Disorders / Q000188:drug therapy*