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A more detailed analysis is presented by Nanos et al. (2004), who fitted ordinary mixed models but applied Kriging methods to the estimated random effects to account for spatial correlation.
According to the fitted ordinary least squares and robust regression models, the equine-assisted activities program had, on average, a large positive effect on children's gross motor development in comparison to the conventional physical education in the control group for 3 months.
In order to compare the distribution of AT-rich motifs associated with positive nucleosomal potential values among groups of genes, we fitted ordinary least squares regression models with robust standard errors, with the number of positive AT-rich motifs as the dependent variable and dummy variables of the corresponding group of genes as predictors for all dipteran species.
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The method fits ordinary QTL and vQTL simultaneously in the same model.
To evaluate possible multicollinearity, we fit ordinary least squares regression models, including all BMI Z-scores during youth visits and BMI at follow-up to calculate variance inflation factors (VIFs).
There was no evidence of strong threshold/nonlinear effects for PM2.5 although nonlinearity was evident among co-pollutants; thus, we fit ordinary least squares regression with piecewise linear functions as appropriate.
Commonly, researchers select reasonable combinations of polynomial age terms to fit ordinary regression models within each child [ 17, 18, 35], or mixed effect models [ 14, 33, 34] among a group of children.
Exploratory analyses will include fitting ordinary least squares regression models to evaluate the association between the primary outcomes and a variety of possible predictors (e.g., baseline T-scores, use of calcium and vitamin D supplements, activity level, Tai Chi compliance, exposure to specific types of Tai Chi exercises, etc).
Just as Joyce fitted an ordinary day in Dublin into the armature of the Odyssey, so Gray reconfigures the life of Duncan Thaw into a polyphonic Divina Commedia of Scotland.
These models were fitted using ordinary least square regression assuming a power function with multiplicative error structure (Lai et al. 2013; Dong et al. 2016).
We first fitted an ordinary linear regression model, which provided an estimated intercept of 16 t/ha and a slope of 13.4 t/ha/m, and had a RMSE of 54.3 t/ha.
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