Man pages for guess
Adjust Estimates of Learning for Guessing

calculate_expected_values	Calculate expected values for goodness of fit test
cell_probs	Model Criticism Tools
class_conditional_item	Class-conditional likelihood for single item
coef.guess_fit	Extract coefficients from guess_fit
count_transitions	Count transitions between pre and post test responses
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
difficulty_to_gamma	Transform difficulty to gamma
dk_cell_probs	Cell probabilities for the model with Don't Know
eq1dk	Constraints: Sum to 1
eqn1	Sum to 1 constraint (no DK)
estimate_logit_score	Estimate a Cross-Sectional Logit Score
extract_params	Extract parameter matrix from lca_result
fit_model	Goodness of fit statistics for transition matrix data
format_transition_matrix	Format transition matrix result with appropriate row and...
gamma_to_difficulty	Transform gamma to difficulty
group_adj	Group Level Adjustment That Accounts for Propensity to Guess
guessdk_lik	guessdk_lik
guess_lik	guess_lik
guess-package	'guess' adjust estimates of learning for guessing related...
individual_likelihood_details	Calculate per-individual log-likelihood
interleave	Interleave vectors
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
make_guessdk_lik_difficulty	Create difficulty-parameterized likelihood function (DK)
make_guess_lik_difficulty	Create difficulty-parameterized likelihood function (no DK)
multinomial_nll	Multinomial negative log-likelihood
multi_transmat	Creates a transition matrix for each item.
new_guess_cv	Create a guess_cv object
new_guess_fit	S3 Methods for guess Objects
nodk_cell_probs	Cell probabilities for the model without Don't Know
nona	Normalize NA Responses
normalize_missing_action	Normalize structural missingness handling
normalize_na_as	Normalize how NA responses are classified
normalize_responses	Normalize raw item responses
perplexity_individuals	Calculate perplexity from individual-level data
perplexity_items	Calculate perplexity from aggregated item data
person_item_expectation	Person/item EM expectation step
person_item_lca_fit	Fit a Joint Person-Level Latent Class Model
person_item_maximization	Person/item EM maximization step
person_item_response_probs	Person/item response probabilities
posterior_class_probs	Compute posterior class probabilities
posterior_learned	Compute posterior probability of learning
prepare_response_data	Normalize paired response data frames
print.guess_cv	Print method for guess_cv
print.guess_fit	Print method for guess_fit
response_to_cell	Map pre/post response pairs to cell indices
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_dataframe	Validate that input is a data frame
validate_dk	Validate dk parameter (knowledge behind don't know responses)
validate_equal_length	Validate that vectors have equal length
validate_gamma	Validate gamma parameter
validate_lucky_vector	Validate lucky vector for standard correction
validate_matrix	Validate matrix input
validate_priors	Validate prior parameters
validate_recovery	Validate Parameter Recovery via Monte Carlo Simulation
validate_required	Validate required parameters are not NULL
validate_subgroup	Validate subgroup parameter
validate_transition_values	Validate transition matrix values
zero1	Constrain vector to [0,1] range