It computes the tetrachoric correlation matrix using the algorithm described in Emrich and Piedmonte (1991). If the resulting matrix is non-positive definite, a nearest positive definite matrix is returned and the warning message will be printed.
● Data Source:
CranContrib
● Keywords:
● Alias: compute.sigma.star
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Checks whether the dimension of marginal probability matrix matches the dimension of correlation matrix.
● Data Source:
CranContrib
● Keywords:
● Alias: conformity.Check
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Generates multivariate ordinal data from the ordinal marginal probabilities and a list returned by the simBinCorr function.
● Data Source:
CranContrib
● Keywords:
● Alias: genOrd
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A package for multivariate ordinal data generation given marginal distributions and correlation matrix based on the methodology proposed by Demirtas (2006).
● Data Source:
CranContrib
● Keywords:
● Alias: MultiOrd, MultiOrd-package
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Validates the range of input matrix of marginal probabilities. It also counts the ordinal categories for each variable.
● Data Source:
CranContrib
● Keywords:
● Alias: validation.ordPmat
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Checks symmetry, positive definiteness, conformity and range of the correlation matrix.
● Data Source:
CranContrib
● Keywords:
● Alias: validation.CorrMat
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Generates multivariate binary data given marginal probabilities and correlation based on algorithm described in Emrich and Piedmonte (1991).
● Data Source:
CranContrib
● Keywords:
● Alias: generate.binary
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Collapses the ordinal categories to binary ones and counts the number of categories in each variable.
● Data Source:
CranContrib
● Keywords:
● Alias: find.binary.prob
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Converts multivariate binary data to multivariate ordinal data using original ordinal probabilities.
● Data Source:
CranContrib
● Keywords:
● Alias: BinToOrd
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Calculates intermediate binary correlation matrix via simulation.
● Data Source:
CranContrib
● Keywords:
● Alias: simBinCorr
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