.mcee_assert_df         Assert that input is a data frame
.mcee_build_f_matrix    Build basis matrix f(t) from time-varying
                        effect formula
.mcee_build_weights     Build per-row weights omega(i,t) for MCEE
                        estimation
.mcee_check_binary_col
                        Validate binary column coding
.mcee_check_control_formula
                        Validate control formula excludes treatment and
                        outcome
.mcee_check_dp_strictly_increasing
                        Check that decision points are strictly
                        increasing within each subject
.mcee_check_formula_mediator
                        Check config formula for inclusion/exclusion of
                        mediator
.mcee_check_id_rows_grouped
                        Check that rows for each subject appear in
                        contiguous blocks
.mcee_check_no_missing_vars
                        Check data frame columns for missing/infinite
                        values
.mcee_check_no_missing_vec
                        Check numeric vector for missing/infinite
                        values
.mcee_check_outcome_constant_within_id
                        Check that outcome is constant within each
                        subject (required for distal outcomes)
.mcee_check_time_varying_effect_form
                        Validate time-varying effect formula structure
.mcee_compact_model_info
                        Generate compact one-line description of
                        nuisance model object
.mcee_core_rows         Numerical core implementing MCEE estimation
                        mathematics
.mcee_default_family    Select default GLM family based on nuisance
                        parameter type
.mcee_drop_var_from_rhs
                        Remove a variable from RHS-only formula
.mcee_fit_nuisance      Fit a single nuisance component with flexible
                        learner support
.mcee_message_if_no_availability_provided
                        Print informative message if no availability
                        column provided
.mcee_print_coef_table
                        Print formatted coefficient table for MCEE
                        results
.mcee_require_cols      Check that required columns exist in data frame
.mcee_resolve_rand_prob
                        Resolve randomization probability from column
                        name or scalar
.mcee_validate_clipping
                        Validate clipping bounds for probability
                        predictions
.mcee_validate_method   Validate that learning method is supported
.mcee_vars_in_config    Extract variables from nuisance configuration
                        formula
.mcee_vars_in_rhs       Extract variable names from RHS-only formula
data_binary             A synthetic data set of an MRT with binary
                        proximal outcomes
data_distal_continuous
                        A synthetic data set of an MRT with continuous
                        distal outcome
data_mimicHeartSteps    A synthetic data set that mimics the HeartSteps
                        V1 data structure to illustrate the use of
                        [wcls()] function for continuous proximal
                        outcomes
data_time_varying_mediator_distal_outcome
                        Example longitudinal dataset with time-varying
                        mediator and distal outcome
dcee                    Distal Causal Excursion Effect (DCEE)
                        Estimation
emee                    Estimates the causal excursion effect for
                        binary outcome MRT
emee2                   Estimates the causal excursion effect for
                        binary outcome MRT
mcee                    Mediated Causal Excursion Effects for MRTs
                        (streamlined)
mcee_config_gam         Configure GAM for MCEE nuisance parameters
mcee_config_glm         Configure GLM for MCEE nuisance parameters
mcee_config_known       Configure known constant values for MCEE
                        nuisance parameters
mcee_config_lm          Configure linear model for MCEE nuisance
                        parameters
mcee_config_maker       Build a nuisance-configuration object for
                        'mcee_general()'
mcee_config_ranger      Configure Ranger Random Forest for MCEE
                        nuisance parameters
mcee_config_rf          Configure Random Forest for MCEE nuisance
                        parameters
mcee_config_sl          Configure SuperLearner for MCEE nuisance
                        parameters
mcee_config_sl_user     Configure SuperLearner with user-specified
                        library for MCEE nuisance parameters
mcee_general            Mediated Causal Excursion Effects (configurable
                        nuisance models)
mcee_helper_2stage_estimation
                        Two-stage helper for mediated causal excursion
                        effects (MCEE)
mcee_helper_stage1_fit_nuisance
                        Fit all nuisance models for MCEE Stage 1
mcee_helper_stage2_estimate_mcee
                        Stage-2 MCEE parameter estimation given
                        nuisance predictions
mcee_userfit_nuisance   Mediated Causal Excursion Effects with
                        user-supplied nuisance predictions
print.summary.mcee_fit
                        Print method for summary of MCEE fits
summary.dcee_fit        Summary for DCEE fits
summary.emee_fit        Summarize Causal Excursion Effect Fits for MRT
                        with Binary Outcomes
summary.mcee_fit        Summarize an mcee fit
summary.wcls_fit        Summarize Causal Excursion Effect Fits for MRT
                        with Continuous Outcomes
wcls                    Estimates the causal excursion effect for
                        continuous outcome MRT
