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In instrumental variable analyses, the results were similar when we used each genotype as an instrument separately, although with lower statistical power (supplementary figure O).
Based on the outcome of the dependent variable analyses, the predictors supplied to the discriminant function classifying concussion history versus no-history control participants were VE and MT in the H condition, and MT in the VRM condition.
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Both variable cluster analysis and individual variable analyses identified the same associations between mood state and chronobiological characteristics (Additional file 1: Table S1).
We conducted intention-to-treat, as-treated, per-protocol, and instrumental variable analyses to analyze the outcome.
Another variable analysed was the relation between the occurrence of back pain and gender.
The single variable analyses are listed in table 1.
All variable analyses were performed by using the SAS 9.2 (SAS Institute Inc., Cary, NC, USA).
Table 4 provides the results of the multi-variable analyses conducted on the PREDICT-D dataset.
Structural equation modelling (SEM) was used to describe relations between HRQoL domains and to estimate a longitudinal Markov model for the variables analysed in the descriptive part.
A breakdown of the different clinical variables analysed and the differences in these variables across the three study groups is given in Additional file 3: Table S3.
Previous results showed that there is an interaction effect between the process variables analysed on the mechanical properties evaluated.
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