efa: Exploratory Factor Analysis Practice Dataset
In doomlab/learnSEM: Learning Tutorials for Structural Equation Modeling

efa	R Documentation

Exploratory Factor Analysis Practice Dataset

Description

Study: This dataset has data on the Openness to Experience scale collected as part of an undergraduate honor's thesis project.

Usage

data(efa)

Format

A data frame with 99 rows and 21 variables.

o1: Believe in the importance of art.
o2: Have a vivid imagination.
o3: Tend to vote for liberal political candidates.
o4: Carry the conversation to a higher level.
o5: Enjoy hearing new ideas.
o6: Enjoy thinking about things.
o7: Can say things beautifully.
o8: Enjoy wild flights of fantasy.
o9: Get excited by new ideas.
o10: Have a rich vocabulary.
o11: Am not interested in abstract ideas.
o12: Do not like art.
o13: Avoid philosophical discussions.
o14: Do not enjoy going to art museums.
o15: Tend to vote for conservative political candidates.
o16: Do not like poetry.
o17: Rarely look for a deeper meaning in things.
o18: Believe that too much tax money goes to support artists.
o19: Am not interested in theoretical discussions.
o20: Have difficulty understanding abstract ideas.
condition: a group condition each participant received

Details

The instructions were: Below are some phrases describing people's behaviors. Please use the rating scale below to describe how accurately each statement describes you. Describe yourself as you generally are now, not as you wish to be in the future. Describe yourself as you honestly see yourself in relation to other people of your gender and of roughly your same age. Please read each statement carefully, and then check the box that corresponds to your response.

Scale: very inaccurate, moderately inaccurate, neither inaccurate nor accurate, moderately accurate, very accurate

doomlab/learnSEM documentation built on Jan. 25, 2024, 2 p.m.