Multiple Correspondence Analysis (CA) and a battery of inference tests via InPosition. The battery includes permutation and bootstrap tests.
epMCA.inference.battery(DATA, make_data_nominal = TRUE, DESIGN = NULL,
make_design_nominal = TRUE, masses = NULL, weights = NULL,
hellinger = FALSE, symmetric = TRUE, correction = c("b"),
graphs = TRUE, k = 0,
test.iters = 100, constrained = FALSE, critical.value = 2)original data to perform a MCA on. This data can be in original formatting (qualitative levels) or in dummy-coded variables.
a boolean. If TRUE (default), DATA is recoded as a dummy-coded matrix. If FALSE, DATA is a dummy-coded matrix.
a design matrix to indicate if rows belong to groups.
a boolean. If TRUE (default), DESIGN is a vector that indicates groups (and will be dummy-coded). If FALSE, DESIGN is a dummy-coded matrix.
a diagonal matrix or column-vector of masses for the row items.
a diagonal matrix or column-vector of weights for the column it
a boolean. If FALSE (default), Chi-square distance will be used. If TRUE, Hellinger distance will be used.
a boolean. If TRUE symmetric factor scores for rows.
which corrections should be applied? "b" = Benz<U+00E9>cri correction, "bg" = Greenacre adjustment to Benz<U+00E9>cri correction.
a boolean. If TRUE (default), graphs and plots are provided (via epGraphs)
number of components to return.
number of iterations
a boolean. If a DESIGN matrix is used, this will constrain bootstrap resampling to be within groups.
numeric. A value, analogous to a z- or t-score to be used to determine significance (via bootstrap ratio).
Returns two lists ($Fixed.Data and $Inference.Data). For $Fixed.Data, see epMCA, coreCA for details on the descriptive (fixed-effects) results.
$Inference.Data returns:
Permutation tests of components. p-values ($p.vals) and distributions of eigenvalues ($eigs.perm) for each component
Bootstrap tests of measures (columns). See boot.ratio.test output details.
Permutation tests of components. p-values ($p.val) and distributions of total inertia ($inertia.perm). This is only useful if corrections are performed. Total inertia is constant for permutation with no corrections in MCA.
epMCA.inference.battery performs multiple correspondence analysis and inference tests on a data matrix.
If the expected time to compute the results (based on test.iters) exceeds 1 minute, you will be asked (via command line) if you want to continue.
# NOT RUN {
data(mca.wine)
mca.wine.res <- epMCA.inference.battery(mca.wine$data)
# }
Run the code above in your browser using DataCamp Workspace