Analysis of complex survey data using SAS.
Commonly used statistical methods and software packages typically assume that observations are independent and identically distributed and fail to account for complex sampling designs when present. I suggest an approach to analyzing complex survey data in SAS, using weighted generalized estimating equations. Limited Monte Carlo simulations support the method. An example demonstrates application of the method and compares results to those from software commonly used in the analysis of complex survey data.
Cole
S R
SR
Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School & Department of Health and Social Behavior, Harvard School of Public Health, 900 Commonwealth Avenue East, Boston, MA 02215, USA. scole@rics.bwh.harvard.edu
D000368:Aged; D001699:Biometry / Q000379:methods*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D009010:Monte Carlo Method; D012984:Software