Literature DB >> 24014144

Longitudinal missing data strategies for substance use clinical trials using generalized estimating equations: an example with a buprenorphine trial.

Sterling McPherson1, Celestina Barbosa-Leiker, Michael McDonell, Donelle Howell, John Roll.   

Abstract

OBJECTIVE: A review of substance use clinical trials indicates that sub-optimal methods are the most commonly used procedures to deal with longitudinal missing information.
METHODS: 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.
RESULTS: 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 (odds ratios (OR) = 0.57, 95% confidence interval (CI): 0.39-0.83), as did the positive UA imputation model (OR = 0.43, CI: 0.34-0.55). The MI model also demonstrated a similar effect of taper group (OR = 0.57, CI: 0.42-0.77), but the effect size was more similar to that of the listwise deletion model.
CONCLUSIONS: 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.
Copyright © 2013 John Wiley & Sons, Ltd.

Entities:  

Keywords:  generalized estimating equations; longitudinal missing data; multiple imputation; positive urine analysis imputation; psychopharmacology clinical trials; substance use disorder treatment

Mesh:

Substances:

Year:  2013        PMID: 24014144      PMCID: PMC3830126          DOI: 10.1002/hup.2339

Source DB:  PubMed          Journal:  Hum Psychopharmacol        ISSN: 0885-6222            Impact factor:   1.672


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