poLCA.simdata
(Package: poLCA) :
Create simulated cross-classification data
Uses the latent class model's assumed data-generating process to create a simulated dataset that can be used to test the properties of the poLCA latent class and latent class regression estimator.
● Data Source:
CranContrib
● Keywords: methods
● Alias: poLCA.simdata
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poLCA.reorder
(Package: poLCA) :
Reorder latent classes in poLCA
A helper function to simplify the reordering of latent classes returned by poLCA.
● Data Source:
CranContrib
● Keywords: methods
● Alias: poLCA.reorder
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poLCA.predcell
(Package: poLCA) :
Predicted cell percentages in a latent class model
Calculates the predicted cell percentages from a latent class model, for specified values of the manifest variables.
● Data Source:
CranContrib
● Keywords: methods
● Alias: poLCA.predcell
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poLCA
(Package: poLCA) :
Latent class analysis of polytomous outcome variables
Estimates latent class and latent class regression models for polytomous outcome variables.
● Data Source:
CranContrib
● Keywords: methods
● Alias: poLCA
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poLCA.entropy
(Package: poLCA) :
Entropy of a fitted latent class model
Calculates the entropy of a cross-classification table produced as a density estimate using a latent class model.
● Data Source:
CranContrib
● Keywords: methods
● Alias: poLCA.entropy
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poLCA.posterior
(Package: poLCA) :
Posterior probabilities from a latent class model
Calculates the posterior probability that cases belong to each latent class.
● Data Source:
CranContrib
● Keywords: methods
● Alias: poLCA.posterior
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poLCA.table
(Package: poLCA) :
Frequency tables of predicted cell counts from latent class analysis
Calculates predicted cell frequencies based on an estimated latent class model.
● Data Source:
CranContrib
● Keywords: methods
● Alias: poLCA.table
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rmulti
(Package: poLCA) :
Random draws from a multinomial distribution
One random draw from a multinomial distribution or list of multinomial distributions.
● Data Source:
CranContrib
● Keywords: methods
● Alias: rmulti
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