A Heap of Trouble? Accounting for Mismatch Bias in Retrospectively Collected Data on Smoking
AbstractWhen 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 to describe our approach, but the method more generally facilitates the use of retrospective data from the multitude of cross-sectional and longitudinal studies worldwide that already have and potentially could collect event data.
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Bibliographic InfoPaper provided by HEDG, c/o Department of Economics, University of York in its series Health, Econometrics and Data Group (HEDG) Working Papers with number 10/20.
Date of creation: Jul 2010
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count data; drinking; endogenous participation; maximum simulated likelihood; sample selection; treatment effects;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-09-11 (All new papers)
- NEP-ECM-2010-09-11 (Econometrics)
- NEP-HEA-2010-09-11 (Health Economics)
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