Methods and analyses {20a, 20b, 20c, 21b}
REGRESSION, SECONDARY
The primary population is the intent‐to‐treat population. This population is defined as all randomized patients with Baseline measurement of the primary endpoint (inclusion criterium). The primary analysis will be done as Baseline‐adjusted analysis of covariance, adjusted for study center with a type 1 error of 0.05 (two‐sided for pairwise comparisons) with primary endpoint FMA‐UE measured at the last therapy visit. The study arm will be coded as a three level factor and in the first step an F‐Test for the overall null hypothesis (all three means are equal) vs. the alternative (at least two measures are different) will be done. If this test is significant, all three pairwise comparisons will be performed without correction for multiple testing. If the F‐Test is not significant, p‐values for pairwise comparisons will be calculated but have to be interpreted descriptively. In the case of a significant result (for the F‐Test) in this step, following the principle of testing hierarchically ordered hypotheses, the same strategy will be applied for follow‐up after three months. For the parameters of interest (effects within study arms and their differences between study arms) two‐sided 95% confidence limits will be calculated. In case of relevant imbalances between study arms regarding known prognostic factors, sensitivity analyses will be done adjusted for these factors. Analogous methods will be applied for the analysis of secondary endpoints (proportional odds model for ordinally scaled variables, logistic regression for binary variables, if possible baseline adjusted). Even though p‐values will be reported, all results have to be interpreted descriptively. Descriptive analyses will include means, standard deviations, and ranges for continuous normally distributed data. Medians and interquartile ranges will be calculated for non‐normally distributed data. Nominal, especially binary variables will be described using absolute and relative frequencies. Additionally, we will present line listings for AEs/SAEs. Missing values of primary and secondary endpoints will be imputed multiply using the method of Rubin. Predictor variables will be age (years), gender, study center and Baseline, which will be available in the intent‐to‐treat population (inclusion criterion). We will use 500 imputation samples; the seed will be the calendarial date of the first programming of the analysis program. An interims analysis is not planned. Exploratory subgroup analyses will be done for gender. Before breaking the code of the randomization a statistical analysis plan will be produced. Deviations from this plan will be documented and justified.. In case of premature termination of study centers or severe imbalance of prognostic factors between study centers, a sensitivity analysis non‐stratified for study centers will be presented.