The impact of loss to follow-up on hypothesis tests of the treatment effect for several statistical methods in substance abuse clinical trials

Sarra L. Hedden, Robert F. Woolson, Rickey E. Carter, Yuko Palesch, Himanshu P. Upadhyaya, Robert J. Malcolm

Research output: Contribution to journalArticle

17 Scopus citations

Abstract

"Loss to follow-up" can be substantial in substance abuse clinical trials. When extensive losses to follow-up occur, one must cautiously analyze and interpret the findings of a research study. Aims of this project were to introduce the types of missing data mechanisms and describe several methods for analyzing data with loss to follow-up. Furthermore, a simulation study compared Type I error and power of several methods when missing data amount and mechanism varies. Methods compared were the following: Last observation carried forward (LOCF), multiple imputation (MI), modified stratified summary statistics (SSS), and mixed effects models. Results demonstrated nominal Type I error for all methods; power was high for all methods except LOCF. Mixed effect model, modified SSS, and MI are generally recommended for use; however, many methods require that the data are missing at random or missing completely at random (i.e., "ignorable"). If the missing data are presumed to be nonignorable, a sensitivity analysis is recommended.

Original languageEnglish (US)
Pages (from-to)54-63
Number of pages10
JournalJournal of Substance Abuse Treatment
Volume37
Issue number1
DOIs
StatePublished - Jul 1 2009

Keywords

  • Hypothesis tests
  • Longitudinal data
  • Loss to follow-up
  • Substance abuse clinical trial
  • Treatment effect

ASJC Scopus subject areas

  • Phychiatric Mental Health
  • Medicine (miscellaneous)
  • Clinical Psychology
  • Psychiatry and Mental health

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