Function reference • celflow

All functions

clean_answers(): Clean and filter survey responses

clean_attention(): Clean Attention Check Failures in a Dataset

clean_ending(): Filter Dataset Based on Ending Status

clean_env(): Clean Global Environment with Exceptions

clean_na(): Clean Dataset Based on Missing Data Threshold and MCAR Test

clean_speed(): Clean Speed Outliers in a Dataset

extract_power(): Extract Power Analysis Results

get_base_names(): Extract Base Names from Dataset Variable Names

get_files(): Retrieve Specified Files from Working Directory

get_git_packages(): Install and Load GitHub Packages

get_means(): Compute Mean Scores for Scales with Optional Reverse Scoring and Clustering

get_packages(): Install and Load R Packages

get_processed_list(): Extract the Most Processed Variables from a List, Optionally Excluding Transformations

get_scale_names(): Create Base Scale Names

get_string(): Convert List to String

get_transformation(): Apply bestNormalize Transformation to Variables in a Dataset and Update Dataset Accordingly

get_winsorization(): Perform Winsorization on a Vector Based on Median Absolute Deviation (MAD)

impute_data(): Impute Data Using MissForest

process_qualtrics_files(): Process Qualtrics Data Files

remove_env_objects(): Remove Specific Objects from Global Environment

report_additional_demographics(): Report Descriptive Statistics for Demographics

root_apply(): Apply a Function to Subset of Variables in a Dataset Based on Root Names

simulate_power(): Compute Power Analysis For SEM Model Using Monte Carlo Simulation