Statistical analyses
aggression, intellectual disabilities
ADVERSE EVENTS, SECONDARY
Characteristics and outcomes were summarised as means with standard deviations (SD) for continuous variables, and as numbers and proportions for categorical variables. Adherence proportion was calculated by dividing the number of days the supplements were offered by the number of days the supplements were taken. The MOAS data was calculated in two ways. First, we summed all counts (number of marks). In addition, the sum of the counts per any of the four types of aggression was calculated (i.e., verbal, against objects, physical and self‐harm). Because of the crossover design, we used a generalised linear mixed model (GLMM). The GLMM was preferred over a generalised linear model (GLM) to allow statistical testing based both on both between‐group and within‐subject variance. Those that crossed‐over were added as repeated measurements in the model. The negative binomial distribution was used for the analyses, since the dispersion statistic of the count data was expected to be higher than one (De Bles et al., For the secondary outcomes, the endpoint minus baseline was calculated and the difference between the active and placebo group was analysed with a linear mixed model analysis. The difference in the number of reported adverse events among the randomised groups was tested with chi‐squared test.The governmental measures on COVID‐19, such as closing down the daycare centers, social distancing, and restricted visiting of family has had an impact on the incidence rate and types of aggression incidents in people with intellectual disabilities (Gleason et al., Blinding was tested by asking participants and support staff at the final assessment in the trial whether they thought participants had been taking the active supplements or the placebo. With chi‐squared test we checked whether participants and staff gave the correct answer more often than expected by chance.Analyses were performed using IBM SPSS statistical software (version 27, IBM Corp Released 2020, IBM SPSS Statistics for Windows), and forest plots and figures using R with RStudio (R version 3.6.0; R Foundation for Statistical Computing, Vienna, Austria, 2016. URL: 