Key points are not available for this paper at this time.
Answers are grounded in this paper and cite their sources.
Supports handling of measurement error in binary outcomes; extends instrumental variable methods from linear to binary regression models.
We describe two approaches to instrumental variable estimation in binary regression measurement error models. The methods entail constructing approximate mean models for the binary response as a function of the measured predictor, the instrument, and any covariates in the model. Estimates are obtained by exploiting relationships between regression parameters, just as in linear instrumental variable estimation. In the course of deriving the approximate mean models, we obtain an alternative characterization of instrumental variable estimation in linear measurement error models.
No takes yet. Share an insight, caveat, or question.
Stefanski et al. (1995) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: