Correcting for measurement error in parametric duration models by quasi-likelihood

In regression models for duration data it is usually implicitly
assumed that all variables are measured and operationalized
exactly. If measurement error is present, however, but not taken
into account, parameter estimates may be severely biased. The
present paper studies measurement error corrected estimation in the
context of a huge class of parametric duration models. The proposed
quasi-likelihood based method easily allows - as long as no
censoring occurs - to deal simultaneously with covariate
measurement error as well as with measurement error in the duration
itself and yields estimates with sound asymptotic properties. A
general formula for the measurement error corrected quasi-score
function can be derived, which is valid for most of the commonly
used parametric duration models.