Errors in variables in panel data with a binary dependent variable

In a conditional logistic regression model for panel data when independent variables are subject to measurement error, the usual estimator, obtained by a regression on the observed independent variables, is asymptotically biased. We introduce a bias-adjusted estimator, which is examined asymptotically under conditions that are appropriate when the measurement error is small but non-negligible.