Measurement error arises when the observed data deviate from true values due to inaccuracies in measurement processes, potentially leading to biased estimates and ...
We develop a model and a numerical estimation scheme for a Bayesian approach to inference in case-control studies with errors in covariables. The model proposed in this paper is based on a ...
Measurement error in exposure assessment is unavoidable. Statistical methods to correct for such errors rely upon a valid error model, particularly regarding the ...
Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 66, No. 1 (2004), pp. 31-46 (16 pages) We suggest two new methods, which are applicable to both deconvolution and ...
Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach ...
In order to measure the mechanical properties of materials in compression, tension, bending or torsion, a universal testing machine is utilized. This article outlines the two different types ...
It supports the two-point calibration practice to minimize errors, particularly at lower concentrations, and recommends measures such as improved aerosol systems and automation to enhance calibration ...
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