diff --git a/dev/.documenter-siteinfo.json b/dev/.documenter-siteinfo.json
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--- a/dev/.documenter-siteinfo.json
+++ b/dev/.documenter-siteinfo.json
@@ -1 +1 @@
-{"documenter":{"julia_version":"1.9.3","generation_timestamp":"2023-09-20T22:49:45","documenter_version":"1.0.1"}}
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+{"documenter":{"julia_version":"1.9.3","generation_timestamp":"2023-09-21T08:07:13","documenter_version":"1.0.1"}}
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diff --git a/dev/api/index.html b/dev/api/index.html
index 3571ff0..5f85cea 100644
--- a/dev/api/index.html
+++ b/dev/api/index.html
@@ -5,24 +5,24 @@
β = [1.,2.],
contrasts=Dict(:cond=>EffectsCoding())
)
-sourceUnfoldSim.MixedModelComponent — Type
A component that adds a hierarchical relation between parameters according to a LMM defined via MixedModels.jl
basis: an object, if accessed, provides a 'basis-function', e.g. hanning(40), this defines the response at a single event. It will be weighted by the model-prediction
formula: Formula-Object in the style of MixedModels.jl e.g. @formula 0~1+cond + (1|subject) - left-handside is ignored
β Vector of betas, must fit the formula
σs Dict of random effect variances, e.g. Dict(:subject=>[0.5,0.4]) or to specify correlationmatrix Dict(:subject=>[0.5,0.4,I(2,2)],...). Technically, this will be passed to MixedModels.jl create_re function, which creates the θ matrices.
contrasts: Dict in the style of MixedModels.jl. Default is empty.
All arguments can be named, in that case contrasts is optional
A component that adds a hierarchical relation between parameters according to a LMM defined via MixedModels.jl
basis: an object, if accessed, provides a 'basis-function', e.g. hanning(40), this defines the response at a single event. It will be weighted by the model-prediction
formula: Formula-Object in the style of MixedModels.jl e.g. @formula 0~1+cond + (1|subject) - left-handside is ignored
β Vector of betas, must fit the formula
σs Dict of random effect variances, e.g. Dict(:subject=>[0.5,0.4]) or to specify correlationmatrix Dict(:subject=>[0.5,0.4,I(2,2)],...). Technically, this will be passed to MixedModels.jl create_re function, which creates the θ matrices.
contrasts: Dict in the style of MixedModels.jl. Default is empty.
All arguments can be named, in that case contrasts is optional
tableModifyFun = x->x; # can be used to sort, or x->shuffle(MersenneTwister(42),x) - be sure to fix/update the rng accordingly!!
tipp: check the resulting dataframe using generate(design)
# declaring same condition both sub-between and item-between results in a full between subject/item design
design = MultiSubjectDesignjectDesign(;
n_items=10,
n_subjects = 30,
subjects_between=Dict(:cond=>["levelA","levelB"]),
items_between =Dict(:cond=>["levelA","levelB"]),
- );
Generates full factorial Dataframe according to MixedModelsSim.jl 's simdatcrossed function Note: nitems = you can think of it as trials or better, as stimuli
Note: No condition can be named dv which is used internally in MixedModelsSim / MixedModels as a dummy left-side
Afterwards applies expdesign.tableModifyFun. Could be used to duplicate trials, sort, subselect etc.
Finally it sorts by :subject
julia> d = MultiSubjectDesign(;nsubjects = 10,nitems=20,both_within= Dict(:A=>nlevels(5),:B=>nlevels(2))) julia> generate(d)
Careful if you modify nitems with nsubjects = 1, n_items has to be a multiple of 4 (or your equivalent conditions factorial, e.g. all combinations length)
overlap = (0.5,0.2), # offset + width/length of Uniform noise. put offset to 1 for no overlap. put width to 0 for no jitter onset=UniformOnset(;offset=sfreq0.5overlap[1],width=sfreq0.5overlap[2]),