Statistical analysis
depression
DISEASE CHARACTERISTIC
Parts of the statistical analyses were conducted using the IBM Statistical Package for the Social Sciences (SPSS) (Version 20) for Windows (IBM, Somers, NY, USA). An intention-to-treat (ITT) approach was used. Descriptive statistics were used to profile the demographic data and disease characteristics as well as quality of life, depression, and stress scores. Baseline values for demographic data, disease characteristics, and quality of life outcome measures between the exercise and control groups were compared using either a Statistical analyses related to modelling the treatment effect were conducted using the programming language R [Linear mixed models assuming Gaussian errors were used to model each response as a function of the main effects: group (a factor with two levels — standard care control and aerobic exercise intervention) and time (a factor with three levels — baseline, 3 months and 6 months). An interaction term (group × time) was also tested for each response. The error term in each model allowed for the correlated nature of the repeated measures recorded on each patient. Different covariance structures were tested and the best structure for each response was selected using restricted maximum likelihood estimation and the corrected Akaike information criterion (AICc) [The effect of exercise adherence on the response was also investigated with adherence to the exercise programme being calculated as the ratio of total completed sessions to total prescribed sessions, expressed as a percentage. The association between exercise adherence and each individual response was tested separately using Pearson’s product-moment correlation. All the tests involved a two-sided significance level of 