Accounting for heaping in retrospectively reported event data - a mixture-model approach

作者：Bar Haim Y^*; Lillard Dean R

来源：Statistics in Medicine, 2012, 31(27): 3347-3365.

DOI：10.1002/sim.5419

• mixture model
• heaping
• empirical Bayes
• retrospective data

When event data are retrospectively reported, more temporally distal events tend to get 'heaped' on even multiples of reporting units. Heaping may introduce a type of attenuation bias because it causes researchers to mismatch time-varying right-hand side variables. We develop a model-based approach to estimate the extent of heaping in the data and how it affects regression parameter estimates. We use smoking cessation data as a motivating example, but our method is general. It facilitates the use of retrospective data from the multitude of cross-sectional and longitudinal studies worldwide that collect and potentially could collect event data.

• 出版日期2012-11-30