After estimation of the model, for each subject the beta parameter for the 1 4 positions was aggregated as a linear "repetition effect" using a [−3, −1, +1, +3] contrast over sequence positions 1 4.
For the categorical variable "type of breast tissue" the beta parameter for the dense or very dense tissue can be interpreted as the average higher pain score in this category compared with women with complete or partly completed involution, corrected for biopsy depth and number of biopsies.
Predicted genome sizes, calculated using the linear models with estimated beta parameters for these five enzymes (table 2), matched actual observed genome size values extremely well (supplementary fig. S3, Supplementary Material online).
The data were used to derive values for the beta parameter of the linear-quadratic equation; the values for the neuroblastomas were higher than for any of the other human tumour cell lines that we have investigated to date.
Beta parameters for each voxel were assessed by multiplying these timeseries with the pseudo-inverse of a temporally filtered design matrix, which was formed by our 5 regressors (indicating sequence positions 1 4 and target trials) convolved with the canonical HRF and by the nuisance parameters.
Specifically, participants showed a significant increase in beta parameter estimates for the differential feedback signal associated with training (Fig. 3; differential signal linear regression: r = 0.83, F 1,10) = 47.39, p < 0.01).
For these purposes, we estimated survival rates of young by fixing the beta parameter in the likelihood function estimated for the covariate "use of AFS" to 0 (see results).
Because the number of completed training runs varied slightly across participants, i.e. participants completed 19 , 20 17, 17, 12, 19, or 22 training runs, the beta parameter estimates for each participant were grouped and averaged into 12 bins (=minimum number of training runs that all participants completed) in a nearest neighbor fashion.
Beta parameter estimates for effects of isochrony versus random timing were extracted for such peak voxels.
Based on the confidence intervals of the beta parameters, survival for size states 1 and 2 did not differ from each other, and survival of size states 2, 3, and 4 did not differ (Table 5).
The backpropagation algorithm was used for the learning process of antecedent fuzzy beta parameters and the consequent part.
