title: Stereotyping and the treatment of missing data for drug and alcohol clinical trials.
abstract: Stigma and stereotyping of marginalized groups often is insidious and shows up in unlikely places, for instance in how clinical trials consider dropouts in treatment research. A surprising number of studies presume that people who do not complete the study protocol relapse and code their data as if they had been observed. There is no good statistical rationale for this treatment of missing data and numerous and more defensible alternative methods are available. We need to be mindful about our attitudes and preconceptions about the people we are intending to help. There is no good reason to continue to support science built on this scientifically indefensible stereotyping, however unintentional.
authors.forename: Stephan
authors.initials: S
authors.lastname: Arndt
mesh_terms: D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D003627:Data Interpretation, Statistical; D006801:Humans; D010352:Patient Dropouts / Q000706:statistics & numerical data*; D011287:Prejudice; D012107:Research Design / Q000706:statistics & numerical data*; D015983:Selection Bias; D013240:Stereotyping; D019966:Substance-Related Disorders / Q000453:epidemiology*