Data management and analysis
REGRESSION
The mean and the relevant standard deviation for presenting patients’ characteristics and the study outcomes were used as summary measures in tables and results. An intention-to-treat analysis was used to manage the missing outcomes. Multiple Imputation technique was applied for addressing the missing observations. MI Impute Chained (MICE) was chosen as an iterative process. Sixteen imputations of variables with missing values on the observed dataset were added. A multiple regression approach for analysis of covariance (ANCOVA) was used to estimate the differences of scores between pre-intervention and post-intervention phases in the two groups. Pre-test scores were considered as a covariate variable and trial intervention as the fixed factor. Also, partial eta squared (η