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A mixed model was used to evaluate the predictor variables.
A linear mixed model was used for statistical analysis while accounting for baseline values where applicable.
A linear mixed model was used to analyze time-course variables.
A linear mixed model was used to assess the predictive values of the parameters.
Mixed model was used to examine the effect of diseases on MY and MEC.
However, for specimens with a bimodal grain size, the fitting of the mixed model was better.
A linear mixed model was used to investigate the possible factors affecting tree loss.
A weighted linear mixed model was used to adjust the spatial variability of surface reflectance.
A secondary linear mixed model was used to simultaneously model the LiDAR variables OV and CC at the plot level.
The linear mixed model was fit, allowing the cut-point to vary from 340 to 370 μm.
To analyze data from human plasma, a linear mixed model was used.
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