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The collection of individual summary maps, for each task and drug condition were then analyzed, voxel-by-voxel, via the flexible factorial model in SPM5 (http://www.fil.ion.ucl.ac.uk/spm) run in Matlab.
For each CNV and each individual a summary signal (e.g median) is calculated when more than one marker is present at the locus of interest.
When calculated at the patient level, they represent each individual's summary of change for a given period of time (as opposed to change at a given time point) and can be treated as raw data for statistical analyses.
The BOLD signals for each subject were analyzed using ICA and post-processed, which led to an individual summary map (see Materials and Methods for details).
A small number of separate statutory offences have been created to cover attempts concerning individual summary offences, in which case, usual attempt law and procedure applies.
In our study, we employed the same strategy to quantify statistical significance of the collection of individual summary maps.
The individual summary statistics images of these four linear contrasts were then entered in second-level analyses, corresponding to random-effects models.
Our approach for estimation of a unified task-related activation map based on one or more task-related ICs for a subject in a fixed task and drug condition, called the individual summary map, is described below.
For further details, see the individual summary Tables 1– 9.
Within the preventive and responsive set, individual summary variables are uncorrelated (by design).
We combined individual summary statistics across the WTCCC RA and UK replication studies using a fixed effects inverse-variance meta-analysis approach for each genic region.
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