epMCA.inference.battery: epMCA.inference.battery: Inference tests for Multiple...

Description Usage Arguments Details Value Author(s) See Also Examples

View source: R/epMCA.inference.battery.R

Description

Multiple Correspondence Analysis (CA) and a battery of inference tests via InPosition. The battery includes permutation and bootstrap tests.

Usage

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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)

Arguments

DATA

original data to perform a MCA on. This data can be in original formatting (qualitative levels) or in dummy-coded variables.

make_data_nominal

a boolean. If TRUE (default), DATA is recoded as a dummy-coded matrix. If FALSE, DATA is a dummy-coded matrix.

DESIGN

a design matrix to indicate if rows belong to groups.

make_design_nominal

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.

masses

a diagonal matrix or column-vector of masses for the row items.

weights

a diagonal matrix or column-vector of weights for the column it

hellinger

a boolean. If FALSE (default), Chi-square distance will be used. If TRUE, Hellinger distance will be used.

symmetric

a boolean. If TRUE symmetric factor scores for rows.

correction

which corrections should be applied? "b" = Benzécri correction, "bg" = Greenacre adjustment to Benzécri correction.

graphs

a boolean. If TRUE (default), graphs and plots are provided (via epGraphs)

k

number of components to return.

test.iters

number of iterations

constrained

a boolean. If a DESIGN matrix is used, this will constrain bootstrap resampling to be within groups.

critical.value

numeric. A value, analogous to a z- or t-score to be used to determine significance (via bootstrap ratio).

Details

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.

Value

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:

components

Permutation tests of components. p-values ($p.vals) and distributions of eigenvalues ($eigs.perm) for each component

fj.boots

Bootstrap tests of measures (columns). See boot.ratio.test output details.

omni

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.

Author(s)

Derek Beaton, Joseph Dunlop, and Hervé Abdi.

See Also

epMCA, epCA, epCA.inference.battery

Examples

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	data(mca.wine)
	mca.wine.res <- epMCA.inference.battery(mca.wine$data)

Example output

Loading required package: prettyGraphs
Loading required package: ExPosition
[1] "It is estimated that your iterations will take 0.62 minutes."
[1] "R is not in interactive() mode. Resample-based tests will be conducted. Please take note of the progress bar."
================================================================================dev.new(): using pdf(file="Rplots1.pdf")
dev.new(): using pdf(file="Rplots2.pdf")
dev.new(): using pdf(file="Rplots3.pdf")

InPosition documentation built on May 2, 2019, 7:59 a.m.