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Statistical analyses were based on linear mixed models.
Jensen et al. (2008) proposed two T2 control charts based on linear mixed model (LMM) to account for the autocorrelation within linear profiles in phase I.
Many recent methods to account for population structure and covariates are based on linear mixed models (LMMs), which are primarily designed for quantitative traits.
Adopting this type of approach, under a model-assisted framework, in this paper we present a class of estimators of the total of the spatial variable, which are based on linear mixed models.
For continuous response variables, statistical analyses will be based on linear mixed models [ 79].
Currently, multilevel analysis based on linear mixed models can be used to delineate these complex relationships and give correct estimation of the effect of factors at different levels.
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bValues are expressed as mean (95% confidence interval) based on linear-mixed effects models.
aThe values were calculated based on a mixed linear model in the TASSEL ver. 4.0 software.
These EQ-5D values were analysed based on a linear mixed model using the MIXED procedure in SAS 9.1 (SAS Institute, Cary, NC, USA).
The methodology involved using simulations based on linear mixed-effects modelling of four plot based surveys.
Repeatabilities were calculated based on linear mixed-effects models fitted by restricted maximum likelihood for all parameters using the rptR package [31] for R 2.10.0 [27].
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