Statistical methods for the analysis of longitudinal data from school-based smoking prevention studies.
The features which make longitudinal data obtained from school-based smoking prevention studies well-suited for efficient analysis by survival analysis methods are discussed. Survival analysis methods, in particular relative risk regression models, are described and illustrated through an example involving data from the Waterloo Smoking Prevention Project--Study 1. Indications of some of the possible applications for these techniques in the evaluation of interventions to prevent smoking and the study of the smoking onset process are provided.
Brown
K S
KS
Department of Statistics and Actuarial Science, University of Waterloo, Ontario, Canada.
Peterson
A V
AV
D000293:Adolescent; D003627:Data Interpretation, Statistical; D006302:Health Services Research; D006801:Humans; D008137:Longitudinal Studies; D010352:Patient Dropouts; D012044:Regression Analysis; D012572:School Health Services / Q000458:organization & administration; D000074606:Smoking Prevention; D012984:Software