  Studies of smoking behavior commonly use the time-line follow-back (TLFB)
method, or periodic retrospective recall, to gather data on daily cigarette
consumption. TLFB is considered adequate for identifying periods of abstinence
and lapse but not for measurement of daily cigarette consumption, thanks to
substantial recall and digit preference biases. With the development of the
hand-held electronic diary (ED), it has become possible to collect cigarette
consumption data using ecological momentary assessment (EMA), or the
instantaneous recording of each cigarette as it is smoked. EMA data, because
they do not rely on retrospective recall, are thought to more accurately
measure cigarette consumption. In this article we present an analysis of
consumption data collected simultaneously by both methods from 236 active
smokers in the pre-quit phase of a smoking cessation study. We define a
statistical model that describes the genesis of the TLFB records as a two-stage
process of mis-remembering and rounding, including fixed and random effects at
each stage. We use Bayesian methods to estimate the model, and we evaluate its
adequacy by studying histograms of imputed values of the latent remembered
cigarette count. Our analysis suggests that both mis-remembering and heaping
contribute substantially to the distortion of self-reported cigarette counts.
Higher nicotine dependence, white ethnicity and male sex are associated with
greater remembered smoking given the EMA count. The model is potentially useful
in other applications where it is desirable to understand the process by which
subjects remember and report true observations.
