A General Framework for Latent Classify and Profile Analysis

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Documentation for package ‘LCPA’ version 1.0.0

• DESCRIPTION file.
• Package NEWS.

Help Pages

adjust.response	Adjust Categorical Response Data for Polytomous Items
check.response	Validate response matrix against expected polytomous category counts
compare.model	Model Comparison Tool
extract	S3 Methods: extract
extract.compare.model	S3 Methods: extract
extract.fit.index	S3 Methods: extract
extract.LCA	S3 Methods: extract
extract.LCPA	S3 Methods: extract
extract.LPA	S3 Methods: extract
extract.LTA	S3 Methods: extract
extract.SE	S3 Methods: extract
extract.sim.LCA	S3 Methods: extract
extract.sim.LPA	S3 Methods: extract
extract.sim.LTA	S3 Methods: extract
get.AvePP	Calculate Average Posterior Probability (AvePP)
get.CEP	Compute Classification Error Probability (CEP) Matrices
get.entropy	Calculate Classification Entropy
get.fit.index	Calculate Fit Indices
get.Log.Lik.LCA	Calculate Log-Likelihood for Latent Class Analysis
get.Log.Lik.LPA	Calculate Log-Likelihood for Latent Profile Analysis
get.Log.Lik.LTA	Calculate Log-Likelihood for Latent Transition Analysis
get.npar.LCA	Calculate Number of Free Parameters in Latent Class Analysis
get.npar.LPA	Calculate Number of Free Parameters in Latent Profile Analysis
get.npar.LTA	Calculate Number of Free Parameters in Latent Transition Analysis
get.P.Z.Xn.LCA	Compute Posterior Latent Class Probabilities Based on Fixed Parameters
get.P.Z.Xn.LPA	Compute Posterior Latent Profile Probabilities Based on Fixed Parameters
get.SE	Compute Standard Errors
install_python_dependencies	Install Required Python Dependencies for Neural Latent Variable Models
Kmeans.LCA	Initialize LCA Parameters via K-means Clustering
LCA	Fit Latent Class Analysis Models
LCPA	Latent Class/Profile Analysis with Covariates
logit	Compute the Logistic (Sigmoid) Function
LPA	Fit Latent Profile Analysis
LRT.test	Likelihood Ratio Test
LRT.test.Bootstrap	Bootstrap Likelihood Ratio Test
LRT.test.VLMR	Lo-Mendell-Rubin likelihood ratio test
LTA	Latent Transition Analysis (LTA)
normalize	Column-wise Z-Score Standardization
plotResponse	Visualize Response Distributions with Density Plots
print	S3 Methods: print
print.compare.model	S3 Methods: print
print.fit.index	S3 Methods: print
print.LCA	S3 Methods: print
print.LCPA	S3 Methods: print
print.LPA	S3 Methods: print
print.LTA	S3 Methods: print
print.SE	S3 Methods: print
print.sim.LCA	S3 Methods: print
print.sim.LPA	S3 Methods: print
print.sim.LTA	S3 Methods: print
print.summary.compare.model	S3 Methods: print
print.summary.fit.index	S3 Methods: print
print.summary.LCA	S3 Methods: print
print.summary.LCPA	S3 Methods: print
print.summary.LPA	S3 Methods: print
print.summary.LTA	S3 Methods: print
print.summary.SE	S3 Methods: print
print.summary.sim.LCA	S3 Methods: print
print.summary.sim.LPA	S3 Methods: print
print.summary.sim.LTA	S3 Methods: print
rdirichlet	Generate Random Samples from the Dirichlet Distribution
sim.correlation	Generate a Random Correlation Matrix via C-Vine Partial Correlations
sim.LCA	Simulate Data for Latent Class Analysis
sim.LPA	Simulate Data for Latent Profile Analysis
sim.LTA	Simulate Data for Latent Transition Analysis (LTA)
summary	S3 Methods: summary
summary.compare.model	S3 Methods: summary
summary.fit.index	S3 Methods: summary
summary.LCA	S3 Methods: summary
summary.LCPA	S3 Methods: summary
summary.LPA	S3 Methods: summary
summary.LTA	S3 Methods: summary
summary.SE	S3 Methods: summary
summary.sim.LCA	S3 Methods: summary
summary.sim.LPA	S3 Methods: summary
summary.sim.LTA	S3 Methods: summary
update	S3 Methods: update
update.LCA	S3 Methods: update
update.LCPA	S3 Methods: update
update.LPA	S3 Methods: update
update.LTA	S3 Methods: update
update.sim.LCA	S3 Methods: update
update.sim.LPA	S3 Methods: update
update.sim.LTA	S3 Methods: update