The outputs are Wald statistics (χ2), indicating the significance, and regression coefficients (B), presenting the relationships between the predictor variables.
Standardized beta coefficients were reported for each predictor variable included in the final reduced models to allow for direct comparison between the predictor variables in the regression model and the criterion variable being studied.
To achieve the best correlation between the predictor variables and the response value, the ACE procedure has the capability of using the independent and dependent variables not only in their actual space but also in their logarithmic space.
To investigate the relationship between the predictor variables of experiential avoidance, relationship satisfaction, prenatal expectations (compared to postnatal experience) and postpartum support, and the criterion variables of maternal attachment, maternal psychological symptoms and maternal responsiveness, after controlling for birth weight.
The strength of association was examined using regression coefficients, P values and adjusted R 2. Standardized beta coefficients were reported for each predictor variable included in the final reduced models to allow for direct comparison between the predictor variables in the regression model and the criterion variable being studied.
We used the Spearman's rank correlation to explore the correlations between the predictor variables.
Excessive multicollinearity between the predictor variables was not detected.
Firstly, simple regression analyses were undertaken between the predictor variables.
This methodology enables a quantitative estimation of relationships between the predictor variables, as well as between the predictor variables and the outcome variable.
We checked for multicollinearity between the predictor variables and none correlated above 0.50.
A Poisson regression model was used to assess the association between the predictor variables and outcomes.
