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Activity Number: 88
Type: Invited
Date/Time: Sunday, August 3, 2014 : 8:30 PM to 10:30 PM
Sponsor: Health Policy Statistics Section
Abstract #314104
Title: Modeling Self-Reported Number of Cigarettes per Day from a Survey of American Indians
Author(s): Hung-Wen Yeh*+ and Byron Gajewski and Won S. Choi and Niaman Nazir and Christine M. Daley
Companies: University of Kansas Medical Center and University of Kansas Medical Center and University of Kansas Medical Center and University of Kansas Medical Center and University of Kansas Medical Center
Keywords: cigarettes per day ; heaping ; inflation models ; negative binomial ; proportional odds model
Abstract:

In tobacco research, smokers often report daily cigarette consumption (cigarettes per day or CPD) by rounding-off integers to the nearest multiples of 5, 10, or 20, instead of the exact number of cigarettes. This phenomenon is known as "heaping" and requires joint modeling of true but unobserved CDP and an assumed heaping pattern, i.e., the relationship between unobserved and self-reported CDP in order to investigate risk factors that may be related to the actual CDP. We present data from a survey of 265 American Indians to investigate the effects of demographic and smoking risk factors on unobserved CDP. The unobserved CDP is modeled by an inflated negative binomial model, and heaping mechanism by a proportional odds model. The predicted values are computed for self-report CDP and the model goodness-of-fit is evaluated by Pearson's statistic.


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