Sentence examples for model analysis with from inspiring English sources

Data were subjected to mixed model analysis with contrasts used to evaluate effect of forage inclusion.

Nonlinear characteristics of ion current signals are identified to cause strong cyclic variations through a single-zone model analysis with different equivalence ratios.

Dry matter intake, milk and component production, body weight, body condition score, as well as DM and NDF digestibility were monitored and assessed using mixed model analysis, with significance declared at P < 0.05.

Change in basilic vein size was modeled using mixed model analysis with a Tukey correction for multiple comparisons to determine if significant differences existed between different maneuvers.

Additionally, small study effect was evaluated by means of visual evaluation of funnel plots and the Egger's test of the intercept, using mortality at discharge from hospital as the main outcome variable and a random effects model analysis, with significant threshold at one-tailed p < 10% as originally described [17].

Mixed model analysis with dam as random effect was used to test for significant differences in egg diameter among strains.

The results from standard linear model analysis (with missing data for three variables) are therefore statistically robust, and are reported here.

Generalized linear mixed-model analysis with Sidak posttest was used to determine the effect of drug treatment on fetal weight of pups from litters of varying size (P < 0.05 was deemed statistically significant).

Estimates of the target intakes (kJ) for protein, fat, and carbohydrate as well as total energy intake of dogs during the ESS of the wet food experiments were determined by mixed-model analysis with dog as a random effect and breed as a fixed effect.

In a mixed-model analysis with time, group, and the component score as the independent variables, the effect of the factor scores was not significant [ F 1, 295.3) = 0.03, p = 0.863], and the variance accounted for was very similar to that for the model containing only time and group.

A second binomial regression run as a mixed-model analysis with genotype included as an additional random effect did not explain significantly more variation in the response (χ1 = 1.87, p = 0.171), and thus genotypic lineage did not predict likelihood of SRE expression.