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Evaluate assumptions

create_transition_matrix()
Create transition matrix for state transitions
coloured_histogram()
Create a Coloured Histogram Highlighting Specific Ranges
coloured_histogram_quantiles()
Visualize Distribution with Automatically Calculated Quantile Highlights
coloured_histogram_sd()
Visualize Distribution with Mean and Standard Deviation Highlights
coloured_histogram_shift()
Visualize Shifts in Data Distributions with Highlighted Ranges
match_mi_general()
General Matching Function for Multiple Imputation Data
transition_table()
Transition Table

Simulate

run_simulations()
Run Simulations for Estimating ATE
simulate_ate_data_with_weights()
Simulate Data for Average Treatment Effect (ATE) with Sample Weights

Prepare data for models

create_ordered_variable()
Create Ordered Variable Based on Quantile Breaks
create_ordered_variable_custom()
Create Ordered Variable with Custom Breaks and Labels
impute_and_combine()
Perform multiple imputation on a list of data frames and combine the results
margot_filter()
Filter Data Based on Exposure Variables
margot_wide()
Transform longitudinal data to wide format with labels
margot_wide_impute_baseline()
Transform to wide data with labels and impute baseline missing values

Estimators

causal_contrast_engine()
Compute Causal Contrasts
causal_contrast_marginal()
Causal Contrast Marginal Effects Estimation
double_robust_marginal()
Double Robust Marginal Estimation and Tabulation

Understand Results

compute_difference()
Compute Difference in Average Treatment Effects or Relative Risk Ratio Between Two Subgroups
group_tab()
Group and Annotate Treatment Effect Estimates
lmtp_evalue_tab()
Calculate E-values for LMTP Output
margot_interpret_table()
Interpret and Describe Causal Effect Estimates Using E-values
margot_lmtp_evalue()
Combine LMTP Summary and E-Value Calculation
margot_lmtp_tab()
Summarise LMTP Output into a Data Frame
tab_engine_marginal()
Tabulate Marginal Effects with E-Values

Visualise Causal Effect Estimates

margot_plot()
Visualise Causal Effect Estimates with Enhanced Flexibility

Utility functions

back_transform_logmean()
Back-transform Log-transformed Mean
back_transform_zscore()
Back Transform Z-Score to Original Scale
construct_formula()
Construct a Formula for Regression Models
here_read()
Read Data Frame from RDS File in a Specified Directory
here_save()
Save Data Frame as RDS File in a Specified Directory
here_read_qs()
Read Data Frame from qs File in a Specified Directory
here_save_qs()
Save Data Frame to qs File in a Specified Directory
pretty_number()
Format Numbers with Commas
remove_numeric_attributes()
Remove Attributes from Numeric Columns in a Data Frame
regress_with_covariates()
Generalized Linear Regression with Covariates
select_and_rename_cols()
Select and Rename Columns Based on Criteria