mixed_descriptor function

Utility function for mixture using mixed description.

This function creates a data.frame ordered by continuous, binary and categorical columns. It also creates a list used if the model uses mixed column types.

mixed_descriptor(data, continuous = NULL, binary = NULL,
                 categorical = NULL, covariate = NULL)

Arguments

• data: Data.frame with the mixed data
• continuous: index or name of continuous column
• binary: index or name of binary column
• categorical: index or name of categorical column
• covariate: index or name of covariate column

Details

This methods returns a list of a data.frame sorted by continuous, binary and categorical columns. It contains also a descriptor that can be used in the measurement section.

Returns

A list containing data and a descriptor.

References

Bolck, A., Croon, M., and Hagenaars, J. Estimating latent structure models with categorical variables: One-step versus three-step estimators. Political analysis, 12(1): 3-27, 2004.

Vermunt, J. K. Latent class modeling with covariates: Two improved three-step approaches. Political analysis, 18 (4):450-469, 2010.

Bakk, Z., Tekle, F. B., and Vermunt, J. K. Estimating the association between latent class membership and external variables using bias-adjusted three-step approaches. Sociological Methodology, 43(1):272-311, 2013.

Bakk, Z. and Kuha, J. Two-step estimation of models between latent classes and external variables. Psychometrika, 83(4):871-892, 2018

Author(s)

Éric Lacourse, Roxane de la Sablonnière, Charles-Édouard Giguère, Sacha Morin, Robin Legault, Félix Laliberté, Zsusza Bakk

Examples

md <- mixed_descriptor(iris, continuous = 1:4, categorical = 5)