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Multiple regression analysis for the detailed body composition characteristics.
Multiple regression analysis for factors associated with OCT4 mRNA expression in neuroblastomas.
Multiple regression analysis for different models was performed to identify the factors influencing work-related burnout.
Multiple regression analysis for the dependent variable fATP identified waist circumference as the independent predictor of fATP (r = 0.65, adjusted r = 0.62, P = 0.001).
Multiple regression analysis for the vegetable-based pattern was positively associated with the female gender, higher educational level, total energy intake, physical activity, higher body mass index (BMI) and never and past smoking.
Multiple regression analysis for both species at constant temperatures indicated that temperature (P < 0·001) and incubation period (P < 0·001) both affected embryo length, as did their interaction (P < 0·001).
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Patients and the reference group will be compared with multiple regression analysis adjusted for age and gender if the assumptions for this model are met.
Multiple regression analysis (MRA) for circadian and sleep predictors over behavioral measures.
Multiple regression analysis accounted for only 44% of the variability in walking speed, and was not statistically significant (p = 0.18).
Then a multiple regression analysis conducted for each combination of Predictor 1 and Predictor 2 provided us with the best predictor for each behavioral parameter with its contribution (defined by the R-squared).
The multiple regression analysis adjusted for age, gender and shift work, showed no association between PER3 polymorphism and MEQ score.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com