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