ValuGaps_Data

This git repo allows you to access the data used in the ValuGaps project and understand the process of creating the dataset. If you only want to download the raw dataset, you can find it on the iData repository [LINK WILL FOLLOW]

If you want to work with the repo, you first have to clone itYou can then run the script clean_data.R to create the dataset used in the ValuGaps project. It will automatically download the data. This is the recommended dataset to use for the project, as it is cleaned and ready to use.

Description of the output

If you run the script clean_data.R, six objects will be created. For choice analysis, use database_main. For everything else use complete_data_main. The other objects are raw_data and all_data, and the main study counterparts from the pre-studies database_prestudies and complete_data_main. raw data is a list that contains the dataset from each survey round. While it is already cleaned, it contains all observations including those that were not complete. all_data is the same as raw_data but merged into one dataframe. Both raw_data and all_data are useful if you want to inspect dropouts or want to include observations that are not complete but may contain the relevant information for your analysis.

@tbl-dataset-summary is a summary of the datasets created by clean_data.R:

Object Name	Description	Format	Usage
database_main	Prepared dataset specifically for choice analysis (observations from the main study waves only).	Dataframe	Choice analysis
complete_data_main	Fully cleaned dataset with only complete observations from the main study waves.	Dataframe	Most analyses (regression, classification, clustering, etc.)
raw_data	A list containing the dataset from each survey round. Includes all observations, even incomplete ones.	List of dataframes	Inspecting dropouts, including incomplete observations for analysis
all_data	Merged version of raw_data into a single dataframe.	Dataframe	Same as raw_data, but structured as one dataset
database_prestudies	Prepared dataset specifically for choice analysis (observations from the pres-study waves only).	Dataframe	Choice analysis
complete_data_prestudies	Fully cleaned dataset with only complete observations from the pre-studies.	Dataframe	Most analyses (regression, classification, clustering, etc.)