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The factor variables and their ranges were: particle size 125 425 μm; temperature 30°C 65°C; impact angle 30° 90°; particle velocity 35 m s−1 55 m s−1; and the baking process applied to the coating.
The results show that attitudinal factor variables and cluster category variables are as important as sociodemographic variables in the models.
The results show that attitudinal factor variables and cluster category variables are as important as sociodemographic variables in models.
All risk factor variables and potential confounders were initially considered using multivariable modified Poisson regression modeling.
Sex, diet, and genotype were factor variables, and their main effects and interactions were estimated in the model.
The Study Factors section is used to record the names of factor variables and the factor type, as shown in Figure 7C.
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The LMERM-analysis includes the fixed variable study treatment, visits as factor variable, and treatment-by-visits interaction (intervention impact).
We fit a linear model treating time as a factor variable and including interaction effects for the GCNF−/− treatment.
The factor variable and the log rank test were used to test the difference between the two groups.
These models also included time since transplant as a factor variable and time varying-covariates, including steroid use and disease status.
The association between probability of offer and group of medical school applied to was evaluated by assessing for interactions between this factor variable and the sociodemographic predictors.
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