A Mixed Modelling Approach for Randomized Experiments with Repeated Measures

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Effects of nitrogen source and rate on productivity and quality of winter oilseed rape (Brassica napus L.) grown in different crop rotations (2005, background): “Mixed modelling provides a flexible framework for randomised experiments with repeated measurements (Piepho et al., 2004).”
Field-based phenomics for plant genetics research (2012, unknown): “Mixed model analysis can account for utocorrelation (Piepho et al., 2004) but may require that plots be ampled using common, fixed time intervals.”
Energy balance of winter oilseed rape (Brassica napus L.) cropping as related to nitrogen supply and preceding crop (2006, methodology): “The model of variance analysis used was adapted from iepho et al. (2004). Mixed modeling provides a flexible frameork for randomized experiments with repeated measurements nd is useful for designs where the repeated factors have few evels, and where each level is observed for all or many of the xper”
Improved evaluation of cover crop species by growth and root factors (2010, methodology): “The correlation structure among repeated measurements in the statistical analysis was described by a first-order autoregressive model (Piepho et al., 2004).”
BLUP for phenotypic selection in plant breeding and variety testing (2008, methodology): “To illustrate formulation of a mixed model, we use the syntax described in Piepho et al. (2003, 2004), which is akin to syntax used in mixed model packages.”