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.