Man pages for tseLCA
Three-Step Estimation for Latent Class Analysis
| 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)... |
| class_sizes | Class sizes and item-response probabilities of the... |
| clean_data | Prepare and validate data for tseLCA estimation |
| coef.tseLCA_structural | Coefficients of a fitted tseLCA model |
| draw_classes | Draw latent class memberships from their marginal... |
| draw_classes_given_Zp | Draw latent classes conditional on the covariate (scenario... |
| draw_indicators | Draw binary indicators given true class memberships |
| draw_Zo | Draw a continuous distal outcome given true class memberships... |
| draw_Zp | Draw the covariate Zp ~ Uniform{1, 2, 3, 4, 5} |
| extract_Y_from_mU | Extract Y.exp, mDesign, posteriors from a multilevLCA mU... |
| fitZ_from_fit0 | Estimate covariate effects with measurement parameters fixed... |
| fitZ_from_multiLCA | Estimate two-step covariate model with multilevLCA (optional... |
| generate_all_conditions | Generate datasets for all 18 conditions in the simulation... |
| generate_data | Generate one dataset following the Bakk & Kuha (2018)... |
| lca_indiv_varmat | Individual-level BHHH variance matrix for binary and... |
| lca_step1 | Fit the LCA measurement model (Step 1) |
| lca_step1_startval | Fit the LCA measurement model from an externally supplied... |
| logLik.tseLCA | Log-likelihood, number of observations, and information... |
| 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... |
| normalize_fitZ_names | Normalize row/column names of a fitZ$mGamma matrix |
| omnibus_test | Omnibus Wald test of class equality for a distal outcome |
| parse_rebase | Parse and validate the rebase argument |
| permute_fit0_classes | Permute class columns of a fit0 object so that class ref_idx... |
| permute_fitZ_classes | Permute class columns of a fitZ object to match a new... |
| plot.tseLCA | Plot item-response probability profiles for a tseLCA model |
| posterior | Posterior class-membership probabilities and modal class... |
| 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... |
| 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) |
| tseLCA | Three-step latent class analysis in one call |
| tseLCA-package | tseLCA: Three-Step Estimation for Latent Class Analysis |
| tse_twostep | Two-step estimation of covariate effects (Bakk and Kuha 2018) |
| vcov.tseLCA_structural | Variance-covariance matrix of a fitted tseLCA model |
