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A significant model effect was found in the expression level among various constructs in both mRNA and protein (P < 0.0001).
A significant model effect was found on the CV of eight constructs that were tested (P < 0.0001).
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Table 2 shows that the type 1 error was close to the nominal level (4.9%-5.8 4.9%-5.8 uterus-model effect was tested in the uterus sub-model and similarly (4.7%-5.7%) when an embryo-model effect was tested in the embryo suterus-model
Based on this unrestricted model selection the model effects were tested for plausibility.
The remaining model effects were included without shape-constraints in the model (Eq. 8).
Model effects were independent of the effects of past sugar consumption.
In modeling using scam an assessment of the unrestricted model effects is part of the model building process, as a decision must be made as to what degree plausible model effects could be forced by imposing restrictions.
Model effects are presented in Table 4.
Firstly, terms in the model (effects) are identified that contribute the largest components to the variance (or equivalently, extract the most overall variation leaving the least residual variance).
Model effects were tested at a significance level of 0.05.
Model effects were considered statistically significant when Type I error rate was less than 5%%.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com