Computational protocol: Cognitive Training and Transcranial Direct Current Stimulation for Mild Cognitive Impairment in Parkinson's Disease: A Randomized Controlled Trial

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Protocol publication

[…] Generalized linear mixed models (GLMMs) analysed outcome variables [] in SPSS version 22.0. Separate GLMMs were run for each outcome variable to optimise the likelihood of convergence. To control the Type 1 error rate and conserve statistical power, outcome variables were grouped by cognitive domain (e.g., executive function and memory) and a more stringent alpha level was applied (p < 0.025) to interaction effects. Each GLMM was assessed for statistically significant Group × Time interaction effects, main effects of Time (per group), and pairwise contrasts. Statistically significant simple main effects of Group were not of interest for this study. Significant simple main effects of Group indicate a significant difference between group outcome scores at either pre-intervention, post-intervention, or follow-up time intervals. However, this study investigated whether there was a significantly different degree of change (over time) on outcome variables, between groups. Therefore, pre-intervention, post-intervention, or follow-up group differences provided no statistical evidence to support the effect of interventions (or no effect of the control group) on outcome variables. Effect sizes (Hedge's g) were calculated using the change score method and represent a comparison between each corresponding intervention group and the control group. Sample size was determined using G∗Power 3. París et al. [] and Naismith et al. [] found moderate to large effect sizes for cognitive outcomes. To detect a moderate effect (power = 0.80 and α = 0.05), 54 participants were required (9 per group). […]

Pipeline specifications

Software tools SPSS, G*Power
Application Miscellaneous