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JSTOR Daily

Nonparametric Identification and Semiparametric Estimation of Classical Measurement Error Models Without Side Information

Virtually all methods aimed at correcting for covariate measurement error in regressions rely on some form of additional information (e.g., validation data, known ...
JSTOR Daily

Correcting for Omitted-Variables and Measurement-Error Bias in Regression with an Application to the Effect of Lead on IQ

Ordinary least squares (OLS) regression estimates are biased, in general, when relevant variables are omitted from the regression equation or when included variables ...
Nature

Measurement Error and Deconvolution Methods

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

Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem

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

Are Labor Market Indicators Telling the Truth? Role of Measurement Error in the U.S. Current Population Survey

Disclaimer: IMF Working Papers describe research in progress by the author (s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the ...
Pew Research Center

Comparing Two Types of Online Survey Samples

Pew Research Center designed this study to assess the current state of online survey sampling methods – both probability-based and opt-in – and determine their accuracy on general population estimates ...