This folder contains the Python script and data used for questionnaire-data cleaning, data reshaping, linear mixed-effects modelling, and figure generation.

Files

analysis_lmm.py
Python script used for all questionnaire-data processing, modelling, and figure generation.

questionnaire raw.xlsx
Anonymized raw questionnaire data. This file is the input file required by the analysis script.

model_output.txt
Saved output from the linear mixed-effects models.

requirements.txt
Required Python packages.

Software Environment

The analysis was conducted in Python. Required packages are listed in requirements.txt.

Reproduction Procedure

1. Install Python 3.
2. Install the required packages:

   pip install -r requirements.txt

3. Place analysis_lmm.py and questionnaire_raw.xlsx in the same folder.
4. Run:

   python analysis_lmm.py

Processing and Analysis

The script screens questionnaire responses according to response duration and straight-line responding. It then reshapes valid responses into long format and calculates the overall score as the mean of the four evaluation dimensions: formal beauty, artistic form, spatial layout, and cultural ambiance.

Linear mixed-effects models are fitted for the overall score and individual evaluation dimensions. Planar position, vertical relationship, and their interaction are included as fixed effects. Participant is included as a random intercept, and scene is included as a variance component. A joint model is also fitted to examine dimension-specific response patterns.

Outputs

The script generates a data-cleaning report, a cleaned long-format questionnaire dataset, model-output text files, and analytical figures in the same folder.