Extending the Box–Cox transformation to the linear mixed model

118 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

From start to finish: a framework for the production of small area official statistics (2018, methodology): “…transformation is defined by Tλ.yik/= ⎧⎨ ⎩ .yik + c/λ −1 κλ−1λ , λ =0, κ log.yik + c/, λ=0, .8/ for yik >−c, where c is a fixed parameter, which makes the data positive to enable the use of the Box–Cox transformation, and κ is the geometric mean of yik (Box and Cox, 1964; Gurka et al., 2006).”
Linguistic pitch analysis using functional principal component mixed effect models (2010, methodology): “This has been previously examined for linear mixed effect models (Gurka et al., 2006).”