The information accumulation process is affected by both within- and between-trial variability and also by an urgency signal.
D2 is the percentage that the between-trial variability constitutes of the sum of the between-trial variability and a sampling error estimate considering the required information size.
However, the information to differentiate between-trial variability and residual variability could be limited and model simulation using the estimated variability should be interpreted with caution.
Thus, for MBMA of ORR or neutropenia rate, data are limited to model both between-trial variability and residual (within-trial) variability.
To estimate a variance of the intervention effect estimates between trials (D = the percentage that the between-trial variability constitutes of the sum of the between-trial variability and a sampling error estimate considering the required information size) [ 25, 26, 52 ].
Our model shares many features with the LIP portion of the model presented by Mazurek et al [23], but we do not directly simulate the sensory inputs from MT. Rather, we simply consider the input to the accumulators to have both within and between trial variability as indicated above.
Statistical evidence for heterogeneity between trials was assessed using the Q-test, and the I index was used as an estimate of the extent of between trial variability.
One could just as well assume random effects for β s (j ); but the RA data does not provide sufficient evidence to inform a between trial variability for b.
For each joint angle, initial value at contact, peak value and between-trial variability was obtained and submitted to a two-way mixed design ANOVA (gender and movement), with movement condition treated as a repeated measure.
Apart from the group variable indicating the use of a PCT algorithm, we included important prognostic factors such as patient age and ARI diagnosis as additional fixed effects; to account for within-and between-trial variability, we added trial to the model as a random effect.
