INCOMPLETE QUALITY-OF-LIFE DATA IN RANDOMIZED TRIALS - MISSING ITEMS

Missing data has been a problem in many quality of life studies. This paper focuses upon the issues involved in handling forms which contain one or more missing items, and reviews the alternative procedures. On e of the most widely practised approaches is imputation using the mean of all observed items in the same subscale. This, together with the r elated estimation of the subscale score, is based upon traditional psy chometric approaches to scale design and analysis. We show that it may be an inappropriate method for many of the items in quality of life q uestionnaires, and would result in biased or misleading estimates. We provide examples of items and subscales which violate the psychometric foundations that underpin simple mean imputation. A checklist is prop osed for examining the adequacy of simple imputation, and some alterna tive procedures are indicated. (C) 1998 John Wiley & Sons, Ltd.