A SAS program for calculating cumulative incidence of events (with confidence limits) and number at risk at specified time intervals with partially censored data

Computer Methods and Programs in Biomedicine

Volumn 89, Issue 1, 2008, Pages 50-55

  Penman, Alan D ^a   Johnson, W D ^b  

^a UNIVERSITY OF MISSISSIPPI SCHOOL OF MEDICINE   (United States)

^b UNIVERSITY OF MISSISSIPPI MEDICAL CENTER   (United States)

Author keywords

Cumulative incidence; Number at risk; Survival data

Indexed keywords

COMPUTATIONAL METHODS; DATA REDUCTION; PROBABILITY DISTRIBUTIONS; TIME AND MOTION STUDY;

ATHEROSCLEROSIS RISK IN COMMUNITIES (ARIC); CUMULATIVE INCIDENCE; SURVIVAL DATA; TIME POINTS;

COMPUTER PROGRAMMING;

ARTICLE; CALCULATION; COMPUTER ANALYSIS; COMPUTER PROGRAM; FOLLOW UP; LONGITUDINAL STUDY; PROBABILITY; PROSPECTIVE STUDY; RISK ASSESSMENT; STATISTICAL ANALYSIS;

AGED; ATHEROSCLEROSIS; COHORT STUDIES; COMPUTATIONAL BIOLOGY; CONFIDENCE INTERVALS; FEMALE; HUMANS; LONGITUDINAL STUDIES; MALE; MIDDLE AGED; PROBABILITY; PROSPECTIVE STUDIES; RISK; SOFTWARE;

EID: 37349087256     PISSN: 01692607     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cmpb.2007.10.004     Document Type: Article

References (10)

1. The LIFETEST Procedure. SAS OnlineDoc 9.1.3. SAS Institute, Cary, NC. Available at: http://support.sas.com/onlinedoc/913/docMainpage.jsp (last accessed July 16, 2007).
2. Ghali W.A., Quan H., Brant R., van Melle G., Norris C.M., Faris P.D., Galbraith P.D., and Knudtson M.L. Comparison of two methods for calculating adjusted survival curves from proportional hazards models. JAMA 286 12 (2001) 1494-1497
3. Lee J., Yoshizawa C., Wilkens L., and Lee H.P. Covariance adjustment of survival curves based on Cox's proportional hazards regression model. Comput. Appl. Biosci. 8 1 (1992) 23-27
4. Nieto F.J., and Coresh J. Adjusting survival curves for confounders: a review and a new method. Am. J. Epidemiol. 143 10 (1996) 1059-1068
5. Pocock S.J., Clayton T.C., and Altman D.G. Survival plots of time-to-event outcomes in clinical trials: good practice and pitfalls. Lancet 359 9318 (2002) 1686-1689
6. SAS Institute, Cary, NC, 2007.
7. The A.R.I.C., and Investigators. The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives. Am. J. Epidemiol. 129 4 (1989) 687-702
8. Fox E.R., Alnabhan N., Penman A., et al. Echocardiographic left ventricular mass index predicts incident stroke in African-Americans: the Atherosclerosis Risk in Communities (ARIC) Study. Stroke 38 (2007) 2686-2691
9. Rosthoj S., Andersen P.K., and Abildstrom S.Z. SAS macros for estimation of the cumulative incidence functions based on a Cox regression model for competing risks survival data. Comput. Methods Programs Biomed. 74 1 (2004) 69-75
10. Satagopan J.M., Ben-Porat L., Berwick M., Robson M., Kutler D., and Auerbach A.D. A note on competing risks in survival data analysis. Br. J. Cancer 91 (2004) 1229-1235