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Statistical significance was assessed with segmented mixed general linear models, analysis of covariance, general estimating equations, χ2, and Fisher's exact procedure.
Statistical analysis was performed using mixed general linear models to evaluate whether the treatment effects on IMT progression rates differed in the two BMI groups.
Using a mixed general linear model (effectively a polynomial regression model), we determined that pain ratings follow a crescendo decrescendo pattern that can be described well using a quadratic model.
Mixed general linear models estimated the effects of NART on cognition and ADL.
Pressure pain measures after drug injection were compared among different drugs using a mixed general linear model with repeated measures.
A mixed general linear model was used to compare the concentrations between the fixed tissue type effect and the random biological repeat (tree) effect.
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Differences in insect abundance, bat activity, and bat species richness were tested using mixed effects general linear models.
A mixed effects General Linear Model will be fitted with residual renal function as the outcome variable and treatment group, time, centre and presence of diabetic nephropathy (Yes/No) as fixed effects terms.
To test for differences between groups in the spatial distribution of submovements and of the velocity profile symmetry index we used a mixed factor general linear model with participants as random factor.
Group statistics were calculated using a paired t-test within a mixed effects general linear model with a cluster forming threshold Z > 2.3, and cluster corrected p value < 0.05 [81].
Data was analysed using two-way mixed factorial ANOVA (General Linear Model).
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