SEARCH

SEARCH BY CITATION

Keywords:

  • Identification;
  • Linear/Nonlinear programming;
  • Randomized studies

Summary.  This article is concerned with drawing inference about aspects of the population distribution of ordinal outcome data measured on a cohort of individuals on two occasions, where some subjects are missing their second measurement. We present two complementary approaches for constructing bounds under assumptions on the missing data mechanism considered plausible by scientific experts. We develop our methodology within the context of a randomized trial of the “Good Behavior Game,” an intervention designed to reduce aggressive misbehavior among children.