anova.tseLCA_covariate
                        Wald tests of covariate terms
as_tse_lca              Use a measurement model with given parameters
                        (Step 1)
best_model              Class enumeration results
bk2018_params           Default population parameters for the Bakk &
                        Kuha (2018) simulation
class_sizes             Class sizes and item-response probabilities of
                        the measurement model
coef.tseLCA_structural
                        Coefficients of a fitted tseLCA model
draw_Zo                 Draw a continuous distal outcome given true
                        class memberships (scenario "distal")
draw_Zp                 Draw the covariate Zp ~ Uniform{1, 2, 3, 4, 5}
draw_classes            Draw latent class memberships from their
                        marginal distribution
draw_classes_given_Zp   Draw latent classes conditional on the
                        covariate (scenario "covariate")
draw_indicators         Draw binary indicators given true class
                        memberships
fitZ_from_fit0          Estimate covariate effects with measurement
                        parameters fixed (two-step EM)
fitZ_from_multiLCA      Estimate two-step covariate model with
                        multilevLCA (optional reference path)
generate_all_conditions
                        Generate datasets for all 18 conditions in the
                        simulation design
generate_data           Generate one dataset following the Bakk & Kuha
                        (2018) simulation design
lca_step1               Fit the LCA measurement model (Step 1)
logLik.tseLCA           Log-likelihood, number of observations, and
                        information criteria
make_rho                Build the item-response probability matrix for
                        the simulation
measurement             Components of a fitted tseLCA model
mnl_probs               Compute multinomial logistic class
                        probabilities given covariates
omnibus_test            Omnibus Wald test of class equality for a
                        distal outcome
plot.tseLCA             Plot item-response probability profiles for a
                        tseLCA model
posterior               Posterior class-membership probabilities and
                        modal class assignments
predict.tseLCA_covariate
                        Class-membership probabilities from a covariate
                        model
predict.tseLCA_measurement
                        Class membership predictions from a measurement
                        model
relevel.tseLCA_covariate
                        Change the reference class of a covariate model
summary.tseLCA_structural
                        Summarize a fitted tseLCA model
three_step              Three-step LCA estimation with covariates
                        and/or distal outcomes
tseLCA                  Three-step latent class analysis in one call
tse_classify            Assign observations to latent classes (Step 2)
tse_control             Estimation settings for tseLCA models
tse_covariate           Relate latent classes to covariates (Step 3)
tse_distal              Relate latent classes to a distal outcome (Step
                        3)
tse_lca                 Fit a latent class measurement model (Step 1)
tse_twostep             Two-step estimates of covariate effects
vcov.tseLCA_structural
                        Variance-covariance matrix of a fitted tseLCA
                        model
