What is the difference between missing completely at random and missing at random?

International Journal of Epidemiology

Volumn 43, Issue 4, 2014, Pages 1336-1339

  Bhaskaran, Krishnan ^a   Smeeth, Liam ^a  

^a LONDON SCHOOL OF HYGIENE AND TROPICAL MEDICINE   (United Kingdom)

Author keywords

Missing at random; Missing data; Multiple imputation

Indexed keywords

AGE; ARTICLE; BLOOD PRESSURE; BODY MASS; CARDIOVASCULAR DISEASE; GENDER; HISTOGRAM; HUMAN; INFORMATION; MEDICAL HISTORY; NAMED GROUPS BY OCCUPATION; NOMENCLATURE; PREGNANCY; PRIORITY JOURNAL; SCIENTIST; STATISTICIAN; METHODOLOGY; STATISTICAL ANALYSIS; STATISTICS;

DATA INTERPRETATION, STATISTICAL; HUMANS; RESEARCH DESIGN; STATISTICS AS TOPIC;

EID: 84905673032     PISSN: 03005771     EISSN: 14643685     Source Type: Journal    
DOI: 10.1093/ije/dyu080     Document Type: Article

References (4)

1. Sterne JA, White IR, Carlin JB et al. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ 2009;338:b2393.
2. Carpenter J, Kenward M. Multiple Imputation and its Application. Chichester, UK: John Wiley&Sons, 2012.
3. Rubin DB. Multiple Imputation for Nonresponse in Surveys. New York: Wiley, 1987.
4. Greenland S, Finkle WD. A critical look at methods for handling missing covariates in epidemiologic regression analyses. Am J Epidemiol 1995;142:1255-64.