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- W3136295245 abstract "The best way to understand a linear mixed modelLinear mixed model , or mixed linear model in some earlier literature, is to first recall a linear regression model. The latter can be expressed as y = Xβ + 𝜖, where y is a vector of observations, X is a matrix of known covariates, β is a vector of unknown regression coefficients, and 𝜖 is a vector of (unobservable random) errors. In this model, the regression coefficients are considered as fixed, unknown constants. However, there are cases in which it makes sense to assume that some of these coefficients are random." @default.
- W3136295245 created "2021-03-29" @default.
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- W3136295245 date "2021-01-01" @default.
- W3136295245 modified "2023-09-29" @default.
- W3136295245 title "Linear Mixed Models: Part I" @default.
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- W3136295245 doi "https://doi.org/10.1007/978-1-0716-1282-8_1" @default.
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