Psychological Pertubation Dataset

This dataset contains data from 30 participants who completed the same questionnaire on meat consumption 12 times. The participant’s opinion was perturbed on each of the 11 items and measured to what extent this changed the participant’s scores on the questionnaire. It is a unique dataset that can be used for several purposes. The questionnaire data can aid research that aims to infer causal relations between variables.

Task: The dataset can be used to study causal discovery.

Summary: 

• Size of dataset: 360 x 11
• Task: Causal Discovery
• Data Type: Discrete
• Dataset Scope: Standalone
• Ground Truth: Known
• Temporal Structure: Static
• License: TBD
• Missing Values: No

Missingness Statement: There are no missing values.

Features: Each measurement is a a six-level factor with levels 1 (completely disagree) to 6 (completely agree)

• moral: Eating meat is morally wrong
• nutr: Meat contains important nutrients for your body
• envir: The production of meat if harmful for the environment
• infer: Animals are inferior to people
• suff: By consuming meat you contribute to animal suffering
• tax: There should be a tax on meat
• taste: I like the taste of meat
• death: Meat reminds me of death and suffering of animals
• sad: If I had to stop eating meat I would feel sad
• guilty: If I eat meat I feel guilty
• disg: If I eat meat I feel disgust

The "Ground Truth" was obtained by the conditional invariant prediction method applied to the data on attitudes of meat consumption.