Human Psychopharmacology: Clinical and Experimental 2013;28(5):506-515. [doi: 10.1002/hup.2339]
Sterling McPherson, PhD (Washington State University, PN Node), Celestina Barbosa-Leiker, PhD (Washington State University, PN Node), Michael McDonell, PhD (University of Washington, PN Node), Donelle Howell, PhD (Washington State University, PN Node), John M. Roll, PhD (Washington State University, PN Node).
A review of substance use clinical trials indicates that sub-optimal methods are the most commonly used procedures to deal with longitudinal missing information. In this study of data from the National Drug Abuse Treatment Clinical Trials Network buprenorphine protocol CTN-0003, listwise deletion (i.e., using complete cases only), positive urine analysis (UA) imputation, and multiple imputation (MI) were used to evaluate the effect of baseline substance use and buprenorphine/naloxone tapering schedule (7 or 28 days) on the probability of a positive UA (UA+) across the 4-week treatment period. The listwise deletion generalized estimating equations (GEE) model demonstrated that those in the 28-day taper group were less likely to submit a UA+ for opioids during the treatment period, as did the positive UA imputation model. The MI model also demonstrated a similar effect of taper group, but the effect size was more similar to that of the listwise deletion model.
Conclusions: The missing data situation described in this investigation generalizes to many other substance use psychopharmacology clinical trials wherein there is missing data on the outcome of interest only. Future researchers may find utilization of the MI procedure in conjunction with the common method of GEE analysis as a helpful analytic approach when the missing at random assumption is justifiable. (Article (Peer-Reviewed), PDF, English, 2013)
Keywords: CTN platform/ancillary study | Data management | Missing data | Urinalysis | Human Psychopharmacology: Clinical and Experimental (journal)
Document No: 991, PMID: 24014144, PMCID: PMC3830126.
Submitted by Sterling McPherson, PhD, PN Node, 9/16/2013.