Sentence examples for model regression was from inspiring English sources

Linear mixed model regression was used to analyze changes over time in plasma FABP levels.

This linear model regression was validated by residual analysis (R2 = 715,415; F1,25 = 30,597 e P << 0,001) as represented in fig. 2B.

Fitting of a linear model regression was then attempted for the full data set (n = 52) initially using ECFC/UCB as a unit of measurement of ECFC frequency.

Count model regression was used in eleven studies, one with outbreaks [ 12] and ten with cases of infections [ 15- 17, 20, 22, 25, 27- 30].

Generalized additive model regression was used to assess the temperature mortality relationship for each grid square, and extract the MMT and the RM25 and RM25/18 (respectively, the ratios of mortality at 25°C/MMT and 25°C/18°C).

GLM model regression was based on a total of 609 assessments of 60 separate videos, excluding second assessments of repeat video pairs; videos with CFT and assessments from an investigator with a large amount of missing data were extracted.

Mixed-model regression was used for the continuous variables, and mixed-model logistic regression was used for the dichotomous variables.

In the GWAS, a linear mixed-model regression was performed, assuming an additive genetic model.

The results of the generalized mixed-model regression are presented in Table 4.

The full-model regressions were followed by separate tests of 42 and 45 °C heat challenge.

Thus reduced major axis regression (RMA, model II regression) is therefore considered more appropriate than model I regression.