Data on the Ten Item Personality Inventory

The Ten Item Personality Inventory (Gosling et al. 2003) is a brief inventory of the Big Five personality domains (Extraversion, Neuroticism, Conscientiousness, Agreeableness, and Openness to experience). This dataset, originally from the Open Source Psychometrics Project (https://openpsychometrics.org/), was used by Jones et al. (2020), from which we obtained this version.

Format

A data frame with 1799 observations on the following 16 variables.

Extraversion: a numeric vector
Neuroticism: a numeric vector
Conscientiousness: a numeric vector
Agreeableness: a numeric vector
Openness: a numeric vector
education: an ordered factor with levels <HS < HS < Univ < Grad
urban: an ordered factor with levels Rural < Suburban < Urban
gender: a factor with levels M F
engnat: a factor with levels Native Non-native
age: a numeric vector
religion: a factor with levels Agnostic Atheist Buddhist Christian (Catholic) Christian (Mormon) Christian (Protestant) Christian (Other) Hindu Jewish Muslim Sikh Other
orientation: a factor with levels Heterosexual Bisexual Homosexual Asexual Other
race: a factor with levels Asian Arab Black Indig-White Other
voted: a factor with levels Yes No
married: a factor with levels Never married Currently married Previously married
familysize: a numeric vector

Source

Jones, P.J., Mair, P., Simon, T. et al. (2020). Network Trees: A Method for Recursively Partitioning Covariance Structures. Psychometrika, 85, 926?945. https://doi.org/10.1007/s11336-020-09731-4

Details

In addition to scores on the Big Five scales, the dataset contains 11 demographic variables on the participants, potentially useful in multivariate analyses.

Scores on each personality domain were calculated by averaging items assigned to each domain (after reverse scoring specific items). In this version, total scores for each scale were calculated by averaging the positively and negatively coded items, for example, TIPI$Extraversion <- (TIPI$E + (8-TIPI$E_r))/2.

Then, for the present purposes, some tidying was done:

100 cases with `gender=="Other" were deleted;
codes for levels of `education`, `engnat` and `race` were abbreviated for ease of use in graphics.

References

Gosling, S. D., Rentfrow, P. J., & Swann, W. B, Jr. (2003). A very brief measure of the Big-Five personality domains. Journal of Research in Personality, 37, 504?528.

Examples


data(TIPI)
# fit an mlm
tipi.mlm <- lm(cbind(Extraversion, Neuroticism, Conscientiousness, Agreeableness, Openness) 
               ~ engnat + gender + education, data = TIPI )
car::Anova(tipi.mlm)
#> 
#> Type II MANOVA Tests: Pillai test statistic
#>           Df test stat approx F num Df den Df    Pr(>F)    
#> engnat     1  0.025927    9.327      5   1752 8.817e-09 ***
#> gender     1  0.088275   33.926      5   1752 < 2.2e-16 ***
#> education  3  0.080337    9.653     15   5262 < 2.2e-16 ***
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

heplot(tipi.mlm, fill=TRUE, fill.alpha=0.1)


pairs(tipi.mlm, fill=TRUE, fill.alpha=0.1)


# candisc works best for factors with >2 levels
library(candisc)
tipi.can <- candisc(tipi.mlm, term="education")
tipi.can
#> 
#> Canonical Discriminant Analysis for education:
#> 
#>      CanRsq Eigenvalue Difference Percent Cumulative
#> 1 0.0740709  0.0799963   0.075792 92.7124     92.712
#> 2 0.0041870  0.0042046   0.075792  4.8730     97.585
#> 3 0.0020791  0.0020834   0.075792  2.4146    100.000
#> 
#> Test of H0: The canonical correlations in the 
#> current row and all that follow are zero
#> 
#>   LR test stat approx F numDF  denDF Pr(> F)    
#> 1      0.92014   9.8819    15 4842.4  <2e-16 ***
#> 2      0.99374   1.3792     8 3510.0  0.2002    
#> 3      0.99792   1.2195     3 1756.0  0.3011    
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

heplot(tipi.can, fill=TRUE, fill.alpha=0.1, 
       var.col = "darkred", var.cex = 1.5, var.lwd = 3)

#> Vector scale factor set to  9.339074