SLM

Synopsis

The core object of the MATLAB BrainStat statistics module (source code).

Usage

obj = SLM(model, contrast, varargin);
obj.fit(data);
  • obj: the SLM object.

  • model: the input model, either a FixedEffect or MixedEffect object.

  • contrast: a contrast in observations of the model.

  • varargin: a set of name-value pairs (see below).

Initialization

A basic SLM object can initialized by simply running it with only a model and contrast i.e. obj = SLM(model, contrast);. However, several name-value pairs can be provided to alter its behavior.

‘cluster_threshold’
  • P-value threshold or statistic threshold for defining clusters, Defaults to 0.001.

‘correction’
  • A cell array containing ‘rft’, ‘fdr’, or both. If ‘rft’ is included, then a random field theory correction will be run. If ‘fdr’ is included, then a false discovery rate correction will be run. Defaults to [].

‘drlim’
  • Step of ratio of variance coefficients, in sd’s. Defaults 0.1.

‘mask’
  • A logical vector containing true for vertices that should be kept during the analysis. Defaults to [].

‘surf’
  • A char array containing a path to a surface, a cell/string array of the aforementioned, or a loaded surface in SurfStat format. Defaults to struct().

‘thetalim’
  • Lower limit on variance coefficients, in sd’s. Defaults 0.01

‘two_tailed’
  • Whether to run one-tailed or two-tailed significance tests. Defaults to true. Note that multivariate models only support two-tailed tests.

Properties

‘cluster_threshold’
  • P-value threshold or statistic threshold for defining clusters, Defaults to 0.001.

‘coef’
  • The coefficients of the model.

‘contrast’
  • The contrast of the model.

‘coord’
  • Vertex coordinates.

‘correction’
  • Correction method for multiple comparisons.

‘df’
  • Degrees of freedom.

‘drlim’
  • Step of ratio of variance coefficients, in sd’s. Defaults 0.1.

‘lat’
  • Lattice structure.

‘mask’
  • A logical vector containing true for vertices that should be kept during the analysis. Defaults to [].

‘model’
  • The model of the SLM.

‘P’
  • The p-values corrected for random field theory.

‘Q’
  • The p-values corrected for false discovery rate.

‘SSE’
  • The sum of squared errors.

‘surf’
  • The surface of the model.

‘t’
  • The t-statistic.

‘thetalim’
  • Lower limit on variance coefficients, in sd’s. Defaults 0.01

‘tri’
  • The surface triangles.

‘two_tailed’
  • Whether to run one-tailed or two-tailed significance tests. Defaults to true. Note that multivariate models only support two-tailed tests.

‘X’
  • The design matrix.