For the cross-over studies, only data from the period before the first cross-over will be analysed.
Changes in quality of life over time will be analysed with linear mixed-effects regression models.
Changes in nutritional status, quality of life and dependence over time will be analysed with linear mixed-effects regression models.
Differences between groups and trends over time will be analysed by means of an analysis of variance for repeated measurements.
The learning curve with implicit versus explicit versus no feedback of the primary outcome measures over time will be analysed using SPSS 18.0 (SPSS Inc., Chicago, IL).
Binary endpoints, such as blood pressure control over time, will be analysed by means of McNemar's test and hierarchical mixed-effects logistic regression models.
The QOL data over time will be analysed by means of a linear mixed effects model including factors for treatment, investigative sites, age groups, and baseline QOL scores.
Severe hypoglycaemic episodes over time will be analysed as Poisson counts using the generalised estimating equations approach to account for correlation among repeated measures within an individual.
Additionally, the relative risk with its respective 95% CIs will be used as measures of effect size and the trends for each variable over time will be analysed using generalised estimation equation (GEE) models.
