Time trends of smoking cessation analyzed with six mathematical survival models.
In this paper, six mathematical models were applied to model time trends of smoking cessation. Both statistical and non-statistical methods were used and included the exponential, ideodynamic, log-logistic, Pareto, sickle and Weibull models. All models included the possibilities of both permanent abstinence and relapse to smoking. Time trends from all models were compared with data from the Multiple Risk Factor Intervention Trial (MRFIT) program. The Pareto, log-logistic, Weibull and ideodynamic models yielded satisfactory fits to the data while the sickle and exponential models did not. Even though the data used in this paper were not sufficient to distinguish among these four models, the methodology will be useful for further narrowing the model choices as additional data for the testing become available.
Elketroussi
M
M
Control Science and Dynamical Systems Center, University of Minnesota, Minneapolis 55455.
Fan
D P
DP
D000328:Adult; D002318:Cardiovascular Diseases / Q000209:etiology / Q000517:prevention & control; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D008403:Mass Screening; D008875:Middle Aged; D008954:Models, Biological; D012008:Recurrence; D012307:Risk Factors; D012907:Smoking / Q000009:adverse effects / Q000401:mortality; D000074606:Smoking Prevention; D016019:Survival Analysis; D013997:Time Factors