Decision Sciences
a year ago

REML algorithm revolutionizes data analysis, unlocking hidden insights in unbalanced datasets.

Oxford University Press eBooks
REML estimation of variance components and analysis of unbalanced designs
R. W. Payne, P. W. Lane, P. G. N. Digby, S A Harding, Peter Leech, G W Morgan, A. Todd, R. Thompson, G. Tunnicliffe Wilson, S. J. Welham, Ronald P. White

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The article discusses a method called REML for estimating variance components and analyzing data with both fixed and random effects. This method can handle unbalanced data sets and identify different sources of variation in the data. The key finding is that REML can accurately estimate treatment effects and variance components in linear mixed models, making it a valuable tool for analyzing complex data in scientific research.