BFI-44 Validation
Description
The Big Five Inventory (BFI-44) was developed by John & Srivastava (1999) as a short measure of the five major dimensions of personality. Participants rated how much each statement applied to them on a scale from 1 (Disagree strongly) to 6 (Agree strongly). The dataset contains 433 respondents.
Items are prefixed by their dimension (Extraversion, Agreeableness, Conscientiousness, Neuroticism, Openness) followed by the item number. Items marked R are reverse-scored before analysis.
John, O. P., & Srivastava, S. (1999). The Big Five trait taxonomy: History, measurement, and theoretical perspectives. In L. A. Pervin & O. P. John (Eds.), Handbook of personality: Theory and research (2nd ed., pp. 102–138). Guilford Press.
Item List
|Label |Dimension |Reverse-scored |Item wording | |:-----|:-----------------|:--------------|:---------------------------------------------| |E01 |Extraversion |FALSE |Is talkative | |A02R |Agreeableness |TRUE |Tends to find fault with others | |C03 |Conscientiousness |FALSE |Does a thorough job | |N04 |Neuroticism |FALSE |Is depressed, blue | |O05 |Openness |FALSE |Is original, comes up with new ideas | |E06R |Extraversion |TRUE |Is reserved | |A07 |Agreeableness |FALSE |Is helpful and unselfish with others | |C08R |Conscientiousness |TRUE |Can be somewhat careless | |N09R |Neuroticism |TRUE |Is relaxed, handles stress well | |O10 |Openness |FALSE |Is curious about many different things | |E11 |Extraversion |FALSE |Is full of energy | |A12R |Agreeableness |TRUE |Starts quarrels with others | |C13 |Conscientiousness |FALSE |Is a reliable worker | |N14 |Neuroticism |FALSE |Can be tense | |O15 |Openness |FALSE |Is ingenious, a deep thinker | |E16 |Extraversion |FALSE |Generates a lot of enthusiasm | |A17 |Agreeableness |FALSE |Has a forgiving nature | |C18R |Conscientiousness |TRUE |Tends to be disorganized | |N19 |Neuroticism |FALSE |Worries a lot | |O20 |Openness |FALSE |Has an active imagination | |E21R |Extraversion |TRUE |Tends to be quiet | |A22 |Agreeableness |FALSE |Is generally trusting | |C23R |Conscientiousness |TRUE |Tends to be lazy | |N24R |Neuroticism |TRUE |Is emotionally stable, not easily upset | |O25 |Openness |FALSE |Is inventive | |E26 |Extraversion |FALSE |Has an assertive personality | |A27R |Agreeableness |TRUE |Can be cold and aloof | |C28 |Conscientiousness |FALSE |Perseveres until the task is finished | |N29 |Neuroticism |FALSE |Can be moody | |O30 |Openness |FALSE |Values artistic, aesthetic experiences | |E31R |Extraversion |TRUE |Is sometimes shy, inhibited | |A32 |Agreeableness |FALSE |Is considerate and kind to almost everyone | |C33 |Conscientiousness |FALSE |Does things efficiently | |N34R |Neuroticism |TRUE |Remains calm in tense situations | |O35R |Openness |TRUE |Prefers work that is routine | |E36 |Extraversion |FALSE |Is outgoing, sociable | |A37R |Agreeableness |TRUE |Is sometimes rude to others | |C38 |Conscientiousness |FALSE |Makes plans and follows through with them | |N39 |Neuroticism |FALSE |Gets nervous easily | |O40 |Openness |FALSE |Likes to reflect, play with ideas | |O41R |Openness |TRUE |Has few artistic interests | |A42 |Agreeableness |FALSE |Likes to cooperate with others | |C43R |Conscientiousness |TRUE |Is easily distracted | |O44 |Openness |FALSE |Is sophisticated in art, music, or literature |
Inter-Item Correlation Matrix
cor_mat <- cor(df[, factor_order], use="pairwise.complete.obs")
cor_long <- melt(cor_mat)
cor_long$Var1 <- factor(cor_long$Var1, levels=factor_order)
cor_long$Var2 <- factor(cor_long$Var2, levels=factor_order)
ggplot(cor_long, aes(x=Var1, y=Var2, fill=value)) +
geom_tile(color="white", linewidth=0.2) +
scale_fill_gradient2(low="#2166ac", mid="white", high="#d6604d",
midpoint=0, limits=c(-1,1), name="r") +
theme_bw(base_size=9) +
theme(axis.text.x=element_text(angle=90, hjust=1, size=7),
axis.text.y=element_text(size=7),
axis.title=element_blank(),
panel.grid=element_blank()) +
ggtitle("BFI-44 inter-item correlation matrix\nItems ordered by dimension; R = reverse-scored")
Subscale Correlations
subscale_scores <- as.data.frame(sapply(names(factors), function(f) {
cols <- item_name_map[sprintf("pers%02d", factors[[f]])]
rowMeans(df[, cols], na.rm=TRUE)
}))
cat("Subscale descriptives\n")## Subscale descriptives
print(psych::describe(subscale_scores))## vars n mean sd median trimmed mad min max range skew kurtosis se ## Extraversion 1 433 3.70 0.85 3.62 3.71 0.93 1.62 5.38 3.75 -0.04 -0.71 0.04 ## Agreeableness 2 433 4.17 0.66 4.22 4.20 0.66 1.89 5.44 3.56 -0.60 0.57 0.03 ## Conscientiousness 3 433 4.11 0.76 4.22 4.14 0.82 2.11 5.44 3.33 -0.40 -0.53 0.04 ## Neuroticism 4 433 3.48 0.83 3.50 3.49 0.93 1.38 5.38 4.00 -0.14 -0.45 0.04 ## Openness 5 433 3.72 0.60 3.70 3.72 0.59 1.80 5.10 3.30 -0.06 -0.35 0.03
cat("\nSubscale intercorrelations\n")## ## Subscale intercorrelations
sub_cor <- round(cor(subscale_scores, use="pairwise.complete.obs"), 2)
print(sub_cor)## Extraversion Agreeableness Conscientiousness Neuroticism Openness ## Extraversion 1.00 0.17 0.14 -0.37 0.26 ## Agreeableness 0.17 1.00 0.44 -0.23 0.20 ## Conscientiousness 0.14 0.44 1.00 -0.21 0.22 ## Neuroticism -0.37 -0.23 -0.21 1.00 -0.14 ## Openness 0.26 0.20 0.22 -0.14 1.00
sub_long <- melt(sub_cor)
ggplot(sub_long, aes(x=Var1, y=Var2, fill=value)) +
geom_tile(color="white", linewidth=0.5) +
geom_text(aes(label=value), size=3.5) +
scale_fill_gradient2(low="#2166ac", mid="white", high="#d6604d",
midpoint=0, limits=c(-1,1), name="r") +
theme_bw(base_size=10) +
theme(axis.title=element_blank(), panel.grid=element_blank()) +
ggtitle("BFI-44 subscale intercorrelations")
Exploratory Factor Analysis (5 Factors)
set.seed(42)
efa <- fa(df, nfactors=5, rotate="oblimin", fm="ml", scores="regression")
print(efa$loadings, cutoff=0.30, sort=TRUE)## ## Loadings: ## ML5 ML1 ML4 ML2 ML3 ## C03 0.689 ## C08R 0.572 ## C13 0.562 ## C18R 0.686 ## C23R 0.623 ## C28 0.619 ## C33 0.663 ## C38 0.521 ## E01 0.787 ## E06R 0.683 ## E21R 0.823 ## E31R 0.608 ## E36 0.664 ## N04 0.513 ## N09R 0.650 ## N14 0.693 ## N19 0.599 ## N24R 0.580 ## N34R 0.571 ## N39 0.509 ## O05 0.513 ## O20 0.514 ## O25 0.533 ## O30 0.528 ## O40 0.607 ## A02R 0.590 ## A07 0.460 ## O10 0.445 ## E11 ## A12R 0.387 ## O15 0.493 ## E16 0.412 0.322 ## A17 ## A22 0.483 ## E26 0.415 -0.384 ## A27R 0.396 ## N29 0.485 ## A32 0.483 ## O35R ## A37R 0.462 ## O41R 0.334 ## A42 0.478 ## C43R 0.472 ## O44 0.476 ## ## ML5 ML1 ML4 ML2 ML3 ## SS loadings 3.732 3.527 3.094 2.650 2.411 ## Proportion Var 0.085 0.080 0.070 0.060 0.055 ## Cumulative Var 0.085 0.165 0.235 0.296 0.350
loadings_mat <- as.data.frame(unclass(efa$loadings))
colnames(loadings_mat) <- paste0("F", 1:5)
loadings_mat$item <- rownames(loadings_mat)
loadings_mat$expected <- item_labels[loadings_mat$item]
load_long <- melt(loadings_mat, id.vars=c("item","expected"),
variable.name="factor", value.name="loading")
load_long$item <- factor(load_long$item, levels=factor_order)
ggplot(load_long, aes(x=factor, y=item, fill=loading)) +
geom_tile(color="white", linewidth=0.3) +
geom_text(aes(label=ifelse(abs(loading)>=0.30, round(loading,2), "")), size=2.5) +
scale_fill_gradient2(low="#2166ac", mid="white", high="#d6604d",
midpoint=0, limits=c(-1,1), name="loading") +
facet_grid(expected ~ ., scales="free_y", space="free_y") +
theme_bw(base_size=9) +
theme(strip.text.y=element_text(angle=0, size=8),
axis.text.y=element_text(size=7),
axis.title=element_blank(),
panel.grid=element_blank()) +
ggtitle("EFA factor loadings (oblimin, ML)\nValues >= |0.30| shown; R = reverse-scored item")
Parallel Analysis
fa.parallel(df, fm="ml", fa="fa",
main="Parallel analysis scree plot (BFI-44)")
## Parallel analysis suggests that the number of factors = 6 and the number of components = NA