Approaches to Missing Data in Substance Abuse Treatment Research

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ECP CoverThis article, currently in-press at Experimental and Clinical Psychopharmacology, was written by Sterling McPherson, Celestina Barbosa-Leiker, G. Leonard Burns, Donelle Howell, and John Roll, all from Washington State University in the Pacific Northwest Node.

It is an ancillary study that used data from protocol CTN-0003 (buprenorphine taper) to compare two common procedures for the treatment of missing information (listwise deletion and positive urine analysis (UA) imputation) to a possible alternative, multiple imputation (MI) procedure.

The analysis determined that although the MI procedure 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 missing data are handled.

Conclusions: 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.

Citation: McPherson S, Barbosa-Leiker C, Burns GL, Howell D, Roll JM. Missing Data in Substance Abuse Treatment Research: Current Methods and Modern Approaches. Experimental and Clinical Psychopharmacology 2012 (in press).


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