Abstract
In most design set-ups such as block designs or row-column designs classification effects such as block effects or row (column) effects are regarded fixed. When these are also considered random variables, we have one or more additional sources of information for estimating treatment effect parameters. Such models are known as mixed effects models. In the experimental designs these were first introduced by Yates (1939).
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© 1989 Springer-Verlag Berlin Heidelberg
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Shah, K.R., Sinha, B.K. (1989). Mixed Effects Models. In: Theory of Optimal Designs. Lecture Notes in Statistics, vol 54. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-3662-7_5
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DOI: https://doi.org/10.1007/978-1-4612-3662-7_5
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