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We modeled weight at 24 months using a mixed model for growth with cubic polynomials, standardizing the children's weights using cohort-specific data.
Variables were analysed using a mixed model.
The data were analyzed using a mixed model analysis.
Data were analyzed using a mixed model procedure.
Data were analyzed with repeated measurements using a mixed model that included the covariate adjustment.
ANOVA was conducted on the experimental data using a mixed model considering the tank effect to be random.
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These 4 patterns were then compared by using a mixed-model analysis of variance.
The influence of sex and exercise on each variable was determined using a mixed-model ANOVA.
Differentially expressed genes were identified using a mixed-model analysis of variance (ANOVA) and linear contrasts (Partek® Infer™ software) as previously reported [15].
Cytokine levels were assessed using a mixed-model longitudinal analysis.
Digenic interactions were also analyzed using a mixed-model approach.
More suggestions(15)
using a combined model
using a mixed models
using a hierarchical model
using a micromechanical model
using a computational model
using a dominant model
using a recessive model
using a conceptual model
using a specific model
using a physical model
using a similar model
using a static model
using a multivariate model
using a different model
using a mixed effect
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