A simulated personality questionnaire in which 400 respondents answer 30
Likert items, six for each of the Big Five personality traits. The data come
in the three pieces that make up a tidymatrix, and can be combined with
tidymatrix(big5_responses, big5_respondents, big5_items).
Format
big5_responsesAn integer matrix with 400 rows (respondents) and 30 columns (items). Values range from 1 (strongly disagree) to 5 (strongly agree). Row and column names are respondent and item IDs.
big5_respondentsA data frame with one row per respondent:
- respondent_id
Respondent ID, e.g.
"R001".- age
Age in years (18–79).
- gender
"Female","Male"or"Non-binary".- education
Highest completed education, a factor with levels Basic < Secondary < Bachelor < Master < PhD.
- occupation
Occupational group, e.g.
"Student","Professional","Retired".- country
Two-letter country code.
- life_satisfaction
Self-rated life satisfaction, 0–10.
- completion_min
Time taken to complete the survey, minutes.
big5_itemsA data frame with one row per item:
- item_id
Item ID: trait letter and number, e.g.
"E1".- trait
Big Five trait measured by the item.
- reversed
TRUEfor reverse-keyed items.- item_text
Statement shown to the respondent.
- position
Position of the item in the questionnaire; traits are interleaved.
Details
The data are simulated, but built to behave like real survey data:
Answers are driven by latent traits, so items of the same trait are correlated and principal components or clustering recover the five traits once reverse-keyed items are re-scored.
Two items per trait are reverse-keyed (
reversed = TRUE); agreeing with them indicates a low trait level.Demographics are internally consistent: education is only possible from a plausible age onwards, students are young and retirees old, and occupation depends on education.
Traits depend on demographics: conscientiousness and agreeableness increase with age while neuroticism decreases; women score higher on neuroticism and agreeableness; openness increases with education and is highest in creative occupations.
Life satisfaction is related to the traits, most strongly (and negatively) to neuroticism.
About 3\ in a few minutes and either gave the same answer to nearly every item or answered at random.
The script that generates the data is in the data-raw folder of the
package source.
See also
big5_countries for country-level information to
join to the respondents.
Examples
tm <- tidymatrix(big5_responses, big5_respondents, big5_items)
tm
#> # A tidymatrix: 400 x 30 matrix
#> # Active: matrix
#> #
#> # Row data: 400 rows x 8 columns
#> # Column data: 30 rows x 5 columns
#> #
#> # Matrix preview:
#> E1 E2 E3 E4 E5 E6 A1 A2 A3 A4 A5 A6 C1 C2 C3 C4 C5 C6 N1 N2 N3 N4 N5 N6 O1
#> R001 4 3 5 3 3 4 3 5 3 4 4 3 1 2 1 2 4 5 3 3 3 2 3 2 2
#> R002 2 4 2 2 3 4 3 2 3 3 2 4 3 4 3 2 4 4 5 4 5 5 2 2 5
#> R003 2 2 3 4 4 3 3 3 4 5 4 3 2 3 1 3 4 4 4 4 3 2 4 2 1
#> R004 2 3 3 3 3 4 3 2 3 2 2 3 3 2 4 2 4 4 5 4 3 3 1 1 4
#> R005 1 2 2 1 5 5 5 5 5 5 2 1 2 5 4 3 2 2 4 2 3 4 3 2 2
#> R006 1 3 3 3 4 3 5 4 5 3 3 2 3 3 1 4 5 5 5 5 5 5 1 1 2
#> O2 O3 O4 O5 O6
#> R001 4 1 3 2 3
#> R002 3 4 5 3 1
#> R003 4 1 2 5 4
#> R004 3 4 4 2 2
#> R005 3 2 3 4 3
#> R006 1 1 1 3 5