This WinterREADME.TXT file was generated on 10/05/2023 by Peter King


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GENERAL INFORMATION
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1. Title of Dataset:
Repo for the data and code for the "Stated preferences for the colours, smells and sounds of biodiversity outweigh those for ecological function. " from the RELATE ERC-funded project.


2. Author Information


  Principal Investigator Contact Information
        Name: Prof. Zoe Davies.
           Institution: University of Kent
           Email: z.g.davies@kent.ac.uk

  Author Contact Information
           Name: Dr. Peter King
           Institution: University of Kent
           Email: p.m.king@kent.ac.uk


3. Date of data collection: 25/01/2021 - 19/02/2021


4. Geographic location of data collection: Great Britain 


5. Information about funding sources that supported the collection of the data:
This work was funded by the European Research Council (ERC) through the Horizon 2020 Research and Innovation Programme (Consolidator Grant no. 726104). 
Analysis used specialist and High-Performance Computing systems provided by Information Services at the University of Kent using RStudio 4.2.0 with Apollo version 0.2.7 (R Core Team, 2021; Hess and Palma, 2019). 


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FILE OVERVIEW
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Folders:
CEModelData: Inputs for estimated models.
CEModelScripts: Scripts to estimate choice models.
CEoutput: Outputs from estimated models, split into models one and two.
OtherData: Inputs to plotting, tables, cleaning and other scripts. Also Winter_dataframe_Step4.csv which is the final output
OutherOutput: Misc tables and figures.
OtherScripts: R scripts to manipulate data, spatial analysis, present outputs, consumer surplus

Scripts:
The workflow to replicate the paper is detailed in 00_Winter_StepByStep.rmd and I have numbered the scripts in the correct order.

Methods for processing the data: 
Survey data collected using Qualtrics and a survey research company. Sample collected using quota sampling. Additional data from ONS.


3. Instrument- or software-specific information needed to interpret the data:
R version 4.2.0 (2022-04-22 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19045)
RStudio 2022.02.2 Build 485 "Prairie Trillium" Release (8acbd38b, 2022-04-19) for Windows