| %!in% | Value matching | 
| abort_argument | Abort based on issues with function argument | 
| abort_argument_class | Abort based on issues with function argument | 
| abort_argument_diff_length | Abort based on issues with function argument | 
| abort_argument_length | Abort based on issues with function argument | 
| abort_argument_type | Abort based on issues with function argument | 
| abort_argument_value | Abort based on issues with function argument | 
| abort_column_not_found | Abort based on column not being found in a data frame | 
| abort_no_method_for_class | Abort method if class is not implemented | 
| abort_package_not_installed | Abort if required package is not installed | 
| accuracy | Model accuracy | 
| accuracy.default | Model accuracy | 
| accuracy.lm | Model accuracy | 
| accuracy.lmerMod | Model accuracy | 
| accuracy.lvmisc_cv | Model accuracy | 
| as_percent | 'percent' vector | 
| bias | Bias | 
| bmi | Compute body mass index (BMI) | 
| bmi_cat | Classify body mass index (BMI) category | 
| center_variable | Center variable | 
| cl | Clear the console | 
| clean_observations | Clean observations | 
| compare_accuracy | Compare models accuracy | 
| create_proj | Create a project | 
| divide_by_quantile | Divide variable based on quantiles | 
| error | Error | 
| error_abs | Absolute error | 
| error_abs_pct | Absolute percent error | 
| error_pct | Percent error | 
| error_sqr | Squared error | 
| get_cv_fixed_eff | Extract information from the trained models from a cross-validation | 
| get_cv_r2 | Extract information from the trained models from a cross-validation | 
| is_outlier | Check whether value is outlier | 
| is_percent | 'percent' vector | 
| le | Last error | 
| lna | Number of elements in a vector. | 
| loa | Limits of agreement | 
| loo_cv | Leave-one-out cross-validation | 
| loo_cv.default | Leave-one-out cross-validation | 
| loo_cv.lm | Leave-one-out cross-validation | 
| loo_cv.lmerMod | Leave-one-out cross-validation | 
| lt | Last error | 
| lunique | Number of elements in a vector. | 
| mean_error | Mean error | 
| mean_error_abs | Mean absolute error | 
| mean_error_abs_pct | Mean absolute percent error | 
| mean_error_pct | Mean percent error | 
| mean_error_sqr | Mean square error | 
| mean_error_sqr_root | Root mean square error | 
| notin | Value matching | 
| pa | Print all rows of a data frame or tibble | 
| percent | 'percent' vector | 
| percent_change | Computes the percent change | 
| plots | Quick plotting | 
| plot_bland_altman | Create a Bland-Altman plot | 
| plot_hist | Quick plotting | 
| plot_line | Quick plotting | 
| plot_model | Plot model diagnostics | 
| plot_model_cooks_distance | Plot model diagnostics | 
| plot_model_multicollinearity | Plot model diagnostics | 
| plot_model_qq | Plot model diagnostics | 
| plot_model_residual_fitted | Plot model diagnostics | 
| plot_model_scale_location | Plot model diagnostics | 
| plot_qq | Quick plotting | 
| plot_scatter | Quick plotting | 
| r2 | Compute R squared | 
| r2.default | Compute R squared | 
| r2.lm | Compute R squared | 
| r2.lmerMod | Compute R squared | 
| repeat_baseline_values | Repeat baseline levels | 
| tb | Capture a backtrace | 
| vif | Variance inflation factor | 
| vif.default | Variance inflation factor | 
| vif.lm | Variance inflation factor | 
| vif.lmerMod | Variance inflation factor |