Imputation is beneficial for handling missing data in predictive models

Journal of Clinical Epidemiology

Volumn 60, Issue 9, 2007, Pages 979-

  Steyerberg, Ewout W ^a   van Veen, Mirjam ^a  

^a ERASMUS MEDICAL CENTER   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

DATA ANALYSIS; FEVER; HOSPITAL ADMISSION; LETTER; LEUKOCYTE; MATHEMATICAL MODEL; MEDICAL INFORMATION; OUTCOME ASSESSMENT; PREDICTION; PRIORITY JOURNAL; STATISTICAL ANALYSIS;

BIAS (EPIDEMIOLOGY); DATA COLLECTION; FORECASTING; HUMANS; MODELS, BIOLOGICAL; MODELS, STATISTICAL;

EID: 34547662843     PISSN: 08954356     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jclinepi.2007.03.003     Document Type: Letter

References (4)

1. Gorelick M.H. Bias arising from missing data in predictive models. J Clin Epidemiol 59 10 (2006) 1115-1123
2. Little R.J.A., and Rubin D.B. Statistical analysis with missing data (1987), Wiley, New York Wiley series in probability and mathematical statistics. Applied probability and statistics
3. Vach W., and Blettner M. Missing data in epidemiologic studies. Encyclopedia of biostatistics (1998), John Wiley & Sons, New York 2641-54
4. Royston P., Altman D.G., and Sauerbrei W. Dichotomizing continuous predictors in multiple regression: a bad idea. Stat Med 25 1 (2006) 127-141