Package index • guess

All functions
`calculate_expected_values()`	Calculate expected values for goodness of fit test
`coef(<guess_fit>)`	Extract coefficients from guess_fit
`cross_sectional_learning()`	Cross-sectional learning estimate
`cross_sectional_learning_score()`	Cross-Sectional Learning Score
`cv_individuals()`	K-fold cross-validation over individuals
`cv_items()`	K-fold cross-validation over items
`estimate_logit_score()`	Estimate a Cross-Sectional Logit Score
`fit_model()` `fit_dk()` `fit_nodk()`	Goodness of fit statistics for transition matrix data
`format_transition_matrix()`	Format transition matrix result with appropriate row and column names
`group_adj()`	Group Level Adjustment That Accounts for Propensity to Guess
`item_lca_fit()`	Fit Independent Item-Wise LCA Models
`lca_adj()`	Person Level Adjustment
`lca_cor()`	Calculate item level and aggregate learning
`lca_difficulty()`	Estimate LCA model with a bounded guessing-probability link
`lca_se()`	Bootstrapped standard errors of effect size estimates
`log_likelihood()`	Calculate log-likelihood for transition data
`multi_transmat()`	Creates a transition matrix for each item.
`nona()`	Normalize NA Responses
`perplexity_individuals()`	Calculate perplexity from individual-level data
`perplexity_items()`	Calculate perplexity from aggregated item data
`person_item_lca_fit()`	Fit a Joint Person-Level Latent Class Model
`posterior_class_probs()`	Compute posterior class probabilities
`posterior_learned()`	Compute posterior probability of learning
`print(<guess_cv>)`	Print method for guess_cv
`print(<guess_fit>)`	Print method for guess_fit
`simulate_lca()`	Simulation Functions for LCA Models
`simulate_lca_dk()`	Simulate Pre-Post Test Data (DK Model)
`stnd_cor()`	Standard Guessing Correction for Learning
`summary(<guess_cv>)`	Summary method for guess_cv
`summary(<guess_fit>)`	Summary method for guess_fit
`transmat()`	transmat: Cross-wave transition matrix
`validate_compatible_dataframes()`	Validate that two data frames have compatible dimensions
`validate_gamma()`	Validate gamma parameter
`validate_lucky_vector()`	Validate lucky vector for standard correction
`validate_priors()`	Validate prior parameters
`validate_recovery()`	Validate Parameter Recovery via Monte Carlo Simulation
`validate_transition_values()`	Validate transition matrix values

Reference

All functions