Both the multivariable models developed using stepwise logistic regression were adjusted for clustering; and furthermore, second model was also adjusted for co-morbidities, i.e. history of coronary heart disease and history of stroke.
Due to the retrospective nature of the data collection, the multivariable models developed in this study can be used to identify risk and protective factors for POV in children after posterior fossa surgery in general.
First we describe two breast cancer datasets used to exemplify a multivariable prognostic model developed on one clinical dataset and evaluated on another.
A simple risk model was developed using baseline HbA1c as the only predictor, and a multivariable model was developed using baseline HbA1c, age, BMI, and systolic blood pressure (SBP) as predictors.
A multivariable model was developed using the same modeling approach described previously to determine the anemia PR for iron deficiency and vitamin A deficiency.
A multivariable model was developed using a forward stepwise approach.
A multivariable model was developed using a forward stepwise based approach.
To identify the association between the use of any bridging anticoagulant and adverse events, a multivariable model was developed.
An initial multivariable model was developed (table 2) that solely included the lifestyle factors followed by a further model adjusting for maternal age, educational level, BMI and ethnicity.
A final multivariable model was developed using age, sex, ethnicity, educational attainment, and BMI; in addition, backward stepwise regression was used that initially included all variables from the models in Table 2 that were significant at P < 0.10 (Table 3).
