Measurement error arises when the observed data deviate from true values due to inaccuracies in measurement processes, potentially leading to biased estimates and ...

In this review of some of the recent work in the study of errors of measurement, attention is centered on the type of mathematical model used to represent errors of measurement, on the extent to which ...

We consider quasilikelihood models when some of the predictors are measured with error. In many cases, the true but fallible predictor is impossible to measure, and ...

Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach ...

The Brookings Institute released a brief this week on deep poverty. The brief repeated two often cited claims: There is reason to be highly skeptical of both of these claims. When looking at ...