Statistical methods
’ distance).Further
REGRESSION, REGRESSION
Participants’ characteristics will be presented as mean ± standard deviation or median for continuous variables. Dichotomous and categorical variables will be shown as absolute numbers and percentages. Chi-square test and, depending on whether normal distribution was present, independent t -test or Mann-Whitney-U test were used to compare groups at baseline.Regression analyses of complete cases with difference of errors in the cycle course (absolute difference T1-T0) as dependent variable and group (IG/aCG) as dichotomous independent variable adjusted for covariates (gender, bicycle type, daily cycled distance, age) were performed to investigate the primary outcome. In addition, to account for the initial error level and the thus resulting potential for improvement, the number of errors at baseline (T0) were included in the linear model. Prior to the analyses, data were checked for normality (Q-Q-Plots, histograms) and outliers (standardized residuals, Cook’ distance).Further, to analyze possible long-term effects of the intervention, we modeled the error differences made at T1 and T2 to baseline (T0) with help of a linear mixed model in order to account for intrasubject variation. In addition to time and group, we again included the initial error level at baseline (T0) and adjusted the model for the same potential confounders as the linear model.IBM SPSS® Statistics for Windows, Version 26 software (IBM Corp., Armonk, NY, U.S.) and R (R-4.1.3) were used for all statistical analyses. To correct for multiple testing, Bonferroni-Holm-adjustment of p-value was applied for chi-square tests or independent t-tests/Mann-Whitney-U test (p ≤ 0.003). The level of significance for regression analysis was set at α = 0.05 and evaluated based on confidence intervals (CI).