vertexEffectSize | R Documentation |
Takes the output of a minc modelling function and computes the unbiased hedges g* and variance of hedges g*
vertexEffectSize(buffer, predictors = NULL) mincEffectSize(buffer, predictors = NULL) anatEffectSize(buffer, predictors = NULL)
buffer |
The results of a vertex/anat/mincLm run |
predictors |
A vector of factor predictor names. By default the effect size be computed for all treatment-coded factor columns. |
This code implements the methods from Nakagawa, S., Cuthill, I.C., 2007. Effect size, confidence interval and statistical significance: a practical guide for biologists. Biol. Rev. Camb. Philos. Soc. 82, 591-05. https://doi.org/10.1111/j.1469-185X.2007.00027.x for computing effect size of group comparisons from a GLM.
For now, interactions are explicitly excluded from being predictors. To get effect size for interactions, use the interaction() function to create a new treatment coded factor to use as a predictor.
A matrix with columns of hedgesg-<factorlevel> and hedgesg_var-<factorlevel> for each factor predictor in the GLM or for each column supplied.
mincEffectSize
: mincEffectSize
anatEffectSize
: anatEffectSize
## Not run: getRMINCTestData() # read the text file describing the dataset gf <- read.csv("/tmp/rminctestdata/test_data_set.csv") # run a linear model relating the data in all voxels to Genotype vs <- mincLm(jacobians_fixed_2 ~ Sex, gf) effectsize <- mincEffectSize(vs) ## End(Not run)
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