Sentence examples for second level model from inspiring English sources

A t-statistic was calculated for every voxel and contrast images were inserted into a random effects second level model (one-sample t-test) for group analyses.

For group analyses, individual contrast images were entered into a second level model using a flexible factorial ANOVA to assess (i) disease-related (between-subject factor Group, levels controls/Parkinson's disease OFF); and (ii) drug-induced (within-subject factor Medication, ON/OFF) effects on the factor Condition (i.e. Tapping/ Free/Intern/Extern.

Second level models (random effects) for each contrast of interest were made using images of the differences between parameter estimates for trial types in a contrast in a one-sample t-test.

Second level models (random effects) for each contrast of interest were made using an ANOVA of the contrast images from each subject's analysis at the first level, correcting for non-sphericity assuming inequality of variance between groups and sessions, and non-independence of error terms.

In the subject-specific first level model, each stimulus onset was modeled by a canonical hemodynamic response function and its temporal derivative.

The crucial analysis step of the fixation-related approach was realized during the subject-specific first level model specification.

For within subject analysis the scanning paradigm was specified in SPM and a first level model estimation was performed.

For each participant and session, 6 covariates representing residual movement-related artifacts, determined by the spatial realignment step, were included in the first level model to capture residual (linear) movement artifacts.

Our first level model and caller wellbeing model (model 3) were also insensitive to the approach used to select model terms, although the model using the attitudes and effectiveness of service characteristics (model 2) showed some sensitivity to model terms when different modelling and selection approaches were used, possibly due to the larger number of inter-related terms considered.

In a second analysis, another first level model was created to investigate differences between old items in the different recollection tasks based on whether the participant had related a word to themselves or Obama during study, irrespective of whether the experimenter or participant had spoken the word out loud.

On the first level, several models are trained on the dataset; on the second level a high-level model combines the first level models in an optimal way.