Test instruments such as oscilloscopes and DMMs (digital multimeters) often let you get the measurement results you need with just the press of a button. But the number on a meter's display or the ...

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

Measurement error in exposure assessment is unavoidable. Statistical methods to correct for such errors rely upon a valid error model, particularly regarding the ...

When gathering a measurement using a spectroscopy instrument, the user wants to be confident in the result. Whether the technique is OES, XRF, or LIBS, or if thickness or composition are measured, the ...

Population abundances are rarely, if ever, known. Instead, they are estimated with some amount of uncertainty. The resulting measurement error has its consequences on ...

Statistical methodology is presented for the regression analysis of multiple events in the presence of random effects and measurement error. Omitted covariates are ...

Very often, in the test and measurement industry, a measurement is made by instrumentation, which is often subject to errors. It is difficult to estimate the true value of the measured quantity given ...

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