We use Monte Carlo simulations and real data to assess the performance of methods dealing with measurement error in investment equations. Our experiments show that fixed effects, error heteroscedasticity, and data skewness severely affect the performance and reliability of methods found in the literature. Estimators that use higher-order moments return biased coefficients for (both) mismeasured...

Traditional clustering methods assume that there is no measurement error, or uncertainty, associated with data. Often, however, real world applications require treatment of data that have such errors. In the presence of measurement errors, well-known clustering methods like k-means and hierarchical clustering may not produce satisfactory results. The fundamental question addressed in this paper...

Phase-measurement interferometry (PM!) techniques enable quantitative measurements to be performed in optical testing, holographic interferometry, and speckle metrology. This paper will present results of error analyses of the most common errors in phase-measurement techniques. These errors include miscalibrated and nonlinear phase shifters, detector nonlinearities, detection quantization, vibr...

Measure errors in economic data are pervasive and nontrivial in size. The presence of measurement errors causes biased and inconsistent parameter estimates and leads to erroneous conclusions to various degrees in economic analysis. The importance of measurement errors in analyzing the empirical implications of economic theories is highlighted in Milton Friedman’s seminal book on the consumption...

Data with acceptable gridded resolution of daily climatic variables are critical for hydrological and water resource modeling. The gauge-based interpolation methods usually used by hydrologic models in general do not cover the spatial heterogeneity of the variability of climatic variables in a catchment. The errors in the interpolated data fields have the potential to significantly bias hydrolo...

BACKGROUND Spatial epidemiology has been aided by advances in geographic information systems, remote sensing, global positioning systems and the development of new statistical methodologies specifically designed for such data. Given the growing popularity of these studies, we sought to review and analyze the types of spatial measurement errors commonly encountered during spatial epidemiological...

This paper discusses some recent laboratory intercomparisions with emphasis on the success of the uncertainty statement to include the reference value. Some factors that affect this capability are discussed. Recently developed national and international standards in the area of measurement uncertainty are presented as resources for industrial metrologists. Introduction The field of metrology ha...