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This is a random for one of 100 CrunchGear iPhone cases and entering is pretty darn simple.
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We included a random intercept for each participant to account for baseline inter-individual differences.
Models were adjusted for patient characteristics and a random effect for practice.
Models incorporated a random intercept for the population and random slopes for the linear and quadratic time effects.
The models included a random intercept for each subject to help account for between-subject variability.
The term b1j is a random intercept for country j, b2jk is a random intercept for the combination of country j and taxonomic group k, and b3ij is a random intercept for farm ij.
Initial models contained both a random intercept for facility (level 3) and a random intercept for subjects (level 2) nested in facilities.
It is straightforward to show that the existence of a random attractor for ϕ is equivalent to the existence of a random attractor for ψ.
A random suggestion for a new X Prize contest category: super-efficient insurance.
A random drawing for those who quit awarded prizes of $2,000, $1,000 and $500.
Instead, it involves a random search for matches between treatments and diseases.
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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