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The first model, an empty model or unconditional model without any exposure variables was specified to decompose the amount of variance that existed at the district level.
The first model, an empty model including only the random effect variable, was used to examine the clustering of the outcome between the 18 HCs.
The first model, an empty or unconditional model without any exposure variables, was specified to decompose the amount of variance that existed between community levels.
For the dependent variable, HP visit, two models were estimated: the intercept-only model, an empty model that contained no covariates, and the full model that included individual variables and the kebeles.
For each of the three dependent variables, we estimated two models: intercept-only model; an empty model that contains no covariates, and a full model that included individual and kebele level variables.
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Our first model was an empty model involving only unstructured, area-level random effects.
The first model was an empty model that only included a random intercept and the outcome variable of unintended pregnancies.
For each of our three dependent variables, we estimated two models: an empty model that contains no covariates, and a full model that included fixed effects at the individual, household, community and state levels, and state-level random effects.
We estimated four models: an empty model that contained no covariates, an individual model that contained individual variables, a community model that included all individual, supervisor and community variables, and a final model that contained all observed variables with the interaction between the number of supervisions received and CHEW health knowledge.
Rabbits were randomly allocated to a treadmill exercise (TRE) group or a sedentary (SED) group and were prepared as either a PGI model or an empty defect (ED) model.
Since the validity of formulas like $\forall x \ Px \rightarrow \exists x Px$ or $\exists x (Px \rightarrow Px)$ is largely a byproduct of what may strike one as an ad hoc stipulation, one may be motivated to expand the range of model-theoretic interpretations in order to allow for a model with an empty domain of discourse.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com