Workshop on Missing Data in Quality of Life Research in Cancer Clinical Trials : Practical and Methodological Issues. Bad Horn, CHE, 1996/07/01.
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.
One of the most widely practised approaches is imputation using the mean of all observed items in the same subscale.
This, together with the related estimation of the subscale score, is based upon traditional psychometric approaches to scale design and analysis.
We show that it may be an inappropriate method for many of the items in quality of life questionnaires, 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 proposed for examining the adequacy of simple imputation, and some alternative procedures are indicated.
Mots-clés Pascal : Donnée manquante, Distribution aléatoire, Essai clinique, Qualité vie, Information incomplète, Appareil circulatoire pathologie, Analyse donnée, Traitement, Homme, SIDA, Virose, Infection, Tumeur maligne, Questionnaire, Immunopathologie, Immunodéficit
Mots-clés Pascal anglais : Missing data, Random distribution, Clinical trial, Quality of life, Incomplete information, Cardiovascular disease, Data analysis, Treatment, Human, AIDS, Viral disease, Infection, Malignant tumor, Questionnaire, Immunopathology, Immune deficiency
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 98-0228438
Code Inist : 002B30A01A2. Création : 11/09/1998.