Random effects model

Résumé

In statistics, a random effects model, also called a variance components model, is a statistical model where the model parameters are random variables. It is a kind of hierarchical linear model, which assumes that the data being analysed are drawn from a hierarchy of different populations whose differences relate to that hierarchy. A random effects model is a special case of a mixed model. Contrast this to the biostatistics definitions, as biostatisticians use "fixed" and "random" effects to respectively refer to the population-average and subject-specific effects (and where the latter are generally assumed to be unknown, latent variables). Qualitative description Random effect models assist in controlling for unobserved heterogeneity when the heterogeneity is constant over time and not correlated with independent variables. This constant can be removed from longitudinal data through differencing, since taking a first difference will remove any time invariant components of

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https://en.wikipedia.org/wiki/Random_effects_model

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Randomness Assists in Wireless Connectivity

Sumit Kumar, Taniya Singh

ICLAB2019

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Culture of preantral follicles in poly(ethylene) glycol-based, three-dimensional hydrogel: a relationship between swelling ratio and follicular developments

Jeffrey Alan Hubbell, Seung Tae Lee

This study was undertaken to examine how the softness of poly(ethylene) glycol (PEG)-based hydrogels, creating a three-dimensional (3D) microenvironment, influences the in vitro growth of mouse ovarian follicles. Early secondary, preantral follicles of 2week-old mice were cultured in a crosslinked four-arm PEG hydrogel. The hydrogel swelling ratio, which relates to softness, was modified within the range 25.7-15.5 by increasing the reactive PEG concentration in the precursor solution from 5% to 15% w/v, but it did not influence follicular growth to form the pseudoantrum (60-80%; p=0.76). Significant (p21.4 yielded better oocyte maturation than other levels, while the highest competence to develop pronuclear and blastocyst formation was detected at 20.6. In conclusion, gel softness, as reflected in swelling ratio, was one of the essential factors for supporting folliculogenesis in vivo within a hydrogel-based, 3D microenvironment. (c) 2014 The Authors. Journal of Tissue Engineering and Regenerative Medicine published by John Wiley & Sons, Ltd.

Wiley-Blackwell2015

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This paper is concerned with the mathematical characterization and wavelet analysis of self-similar random vector fields. The study consists of two main parts: the construction of random vector models on the basis of their invariance under coordinate transformations, and a study of the consequences of conducting a wavelet analysis of such random models. In the latter part, after briefly examining the effects of standard wavelets on the proposed random fields, we go on to introduce a new family of Laplacian-like vector wavelets that in a way duplicate the covariant-structure and whitening relations governing our random models.

SPIE2009

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