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Results correspond well with predictions of a previous microstructurally-based model for effects of tissue mechanical deformations on glycosaminoglycan architecture and cartilage hydraulic permeability.
The model for effects on BCS included month of insemination, bST and the interaction.
The model for effects on vaginal temperature included bST, cow (bST), day, time of day, and all two way interactions.
Being closely related to the model crucifer A.thaliana, B.napus serves as appropriate model for effects of allopolyploidy [ 16– 16].
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Although the document is a statement of principles, not enforceable regulations, the Canadian experience is instructive; it can be examined as a possible model for effecting change.
Results of model for effect of variables on context-dependent mutation rates of focal nucleotide.
The random effects model for pooling effects was preferred and always used if heterogeneity of treatment effects was present.
These include generation of emissions data, linking of models for different physical compartments as well as to development and application of models for effects and risks.
Logistic regression models were used to test the effect of microsite characteristics on seedling occurrence, and general linear models for effects on seedling height growth and biomass increment.
Therefore, treatment effects were assumed to be not homogeneous among the studies considered, and a random effects model for combining effects of all studies was applied.
The random effect model for pooling effect sizes may be appropriate in this context, since it assumes an underlying variation of the true effect size across different settings.
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