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A multi-center study has been set up to accurately characterize the optical properties of diffusive liquid phantoms based on Intralipid and India ink at near-infrared (NIR) wavelengths. Nine research laboratories from six countries adopting different measurement techniques, instrumental set-ups, and data analysis methods determined at their best the optical properties and relative uncertainties of diffusive dilutions prepared with common samples of the two compounds. By exploiting a suitable statistical model, comprehensive reference values at three NIR wavelengths for the intrinsic absorption coefficient of India ink and the intrinsic reduced scattering coefficient of Intralipid-20% were determined with an uncertainty of about 2% or better, depending on the wavelength considered, and 1%, respectively. Even if in this study we focused on particular batches of India ink and Intralipid, the reference values determined here represent a solid and useful starting point for preparing diffusive liquid phantoms with accurately defined optical properties. Furthermore, due to the ready availability, low cost, long-term stability and batch-to-batch reproducibility of these compounds, they provide a unique fundamental tool for the calibration and performance assessment of diffuse optical spectroscopy instrumentation intended to be used in laboratory or clinical environment. Finally, the collaborative work presented here demonstrates that the accuracy level attained in this work for optical properties of diffusive phantoms is reliable.

Pooling information from multiple, independent studies (meta-analysis) adds great value to medical research. Random effects models are widely used for this purpose. However, there are many different ways of estimating model parameters, and the choice of estimation procedure may be influential upon the conclusions of the meta-analysis. In this paper, we describe a recently proposed Bayesian estimation procedure and compare it with a profile likelihood method and with the DerSimonian-Laird and Mandel-Paule estimators including the Knapp-Hartung correction. The Bayesian procedure uses a non-informative prior for the overall mean and the between-study standard deviation that is determined by the Berger and Bernardo reference prior principle. The comparison of these procedures focuses on the frequentist properties of interval estimates for the overall mean. The results of our simulation study reveal that the Bayesian approach is a promising alternative producing more accurate interval estimates than those three conventional procedures for meta-analysis. The Bayesian procedure is also illustrated using three examples of meta-analysis involving real data. Copyright © 2016 John Wiley & Sons, Ltd.

The Joint Committee for Guides in Metrology, Working Group 1, JCGM-WG1, is currently revising the ‘Guide to the Expression of Uncertainty in Measurement’. In this communication, the motivation for undertaking such a revision is given and the main changes with respect to the current, 2008 edition are outlined.

Scatterometry is frequently used as a non-imaging indirect optical method to reconstruct the critical dimensions (CD) of periodic nanostructures. A particular promising direction is EUV scatterometry with wavelengths in the range of 13 - 14 nm. The conventional approach to determine CDs is the minimization of a least squares function (LSQ). In this paper, we introduce an alternative method based on the maximum likelihood estimation (MLE) that determines the statistical error model parameters directly from measurement data. By using simulation data, we show that the MLE method is able to correct the systematic errors present in LSQ results and improves the accuracy of scatterometry. In a second step, the MLE approach is applied to measurement data from both extreme ultraviolet (EUV) and deep ultraviolet (DUV) scatterometry. Using MLE removes the systematic disagreement of EUV with other methods such as scanning electron microscopy and gives consistent results for DUV.