Calculate scale scores on the Personality Inventory for DSM-5: full version (PID-5, 220 items), short form version (PID-5-SF, 100 items), brief form version (PID-5-BF, 25 items), modified brief form (PID5BF+M, 36 items; Bach et al., 2020), Informant Form (PID-5-IRF, 218 items; Markon et al., 2013), or Forensic Faceted Brief Form (PID-5-FFBF, 100 items; Niemeyer et al., 2022) from item-level data.
Arguments
- data
A data frame containing (at least) all the PID items (numerically scored and in order).
- items
A vector of column names (as strings) or numbers (as integers) corresponding to the PID items in order. Items must be supplied in instrument order; a misordered mapping silently scores the wrong items, so a warning is issued when the names share a common prefix and trailing number but those numbers are not ascending. Duplicated entries are an error. Each column must be numeric or logical, or character holding only numbers (blank cells and
NAvalues count as missing, but the text"NA"is refused). A haven labelled column is read as its plain values. Any other column, such as the choice text of an online export or a factor, is an error of classhitop_nonnumeric_items. So is a 64-bit integer (integer64) column, and, in a UTF-8 session, a column holding text that is not valid UTF-8 (text marked Latin-1 is read as its text); convert such text withiconv(). So is an SPSS column (haven_labelled_spss) that holds a value it declares missing; turn those codes intoNAwithhaven::zap_missing()first. A declared value that is blank is not refused, since blank cells count as missing. The SPSS class of haven before 2.0 (labelled_spss) is refused the same way, buthaven::zap_missing()leaves it unchanged, so set the values itsna_valuesorna_rangeattribute declares toNAfirst.- version
A string indicating the version of the PID to score: "FULL", "SF", "BF", "BFPM" (the 36-item PID5BF+M), "IRF" (the 218-item Informant Form), or "FFBF" (the 100-item Forensic Faceted Brief Form). Only a full name is accepted, in any letter case. Any other value, a start of a name such as
"F"included, is an error of classhitop_unknown_version. (default ="FULL")- srange
An optional numeric vector specifying the minimum and maximum values of the items, used for reverse-coding. (default =
c(0, 3))- prefix
An optional string to add before each scale column name. If no prefix is desired, set to an empty string
"". (default ="pid_")- missing
A string selecting how missing item responses are handled when computing scale scores.
"apa"(the default) follows the published APA scoring key: a facet or domain-item scale with more than 25% of its items unanswered is set toNA, and otherwise the raw score is prorated to the full item count and rounded to the nearest whole number before averaging (a FULL, SF, IRF, FFBF or BFPM domain isNAif any one of its three contributing facets isNA). The PID-5-IRF key prints this step as "round up to the nearest whole number". The package reads it as the nearest-whole-number rule that every other APA PID-5 key states, so an informant facet prorates exactly as the matching self-report facet does. A prorated half rounds away from zero, which is up for the default 0 to 3 coding and down for a negative score under a negativesrange."available"averages whatever items are present (rowMeans(na.rm = TRUE))."complete"returnsNAfor any scale with a missing item (rowMeans(na.rm = FALSE)). With no missing items the three agree. (default ="apa")- calc_se
Deprecated. This argument, and the
_secolumns it adds, will be removed in a future release; a call withcalc_se = TRUEwarns; the warning is classedhitop_deprecated_calc_se, so a caller can silence it by name. This package has no interval function for the PID-5, so there is no replacement for it on this instrument; for measurement precision seereliability_pid5(). What it does while it lasts: an optional logical indicating whether to calculate a standard error for each scale score. For the facets, and for the brief form's domains and total, this is the SD of the items the respondent actually answered divided by the square root of how many of those items they answered. The FULL, SF, IRF, FFBF and BFPM domain scores are means of three facet scores rather than of items, so their standard errors are taken one level up: the SD of the three contributing facet scores divided by the square root of 3. Standard errors areNAwherever their scale score isNA. A BFPM facet scored from one answered item undermissing = "available"has a score but anNAstandard error, because the SD of one value is undefined. Each one summarizes how much a respondent's answers varied within a scale. It is not a standard error of measurement — no reliability estimate enters it — so it does not give a confidence interval for a respondent's true score; for measurement precision seereliability_pid5(). (default =FALSE)- append
An optional logical indicating whether the new columns should be added to the end of the
datainput. (default =TRUE)
Value
A tibble containing all scale scores and standard
errors (if requested) and all original data columns (if requested)
Details
For the FULL, SF and IRF versions, the output includes the 25 facet
scores followed by the 5 personality-trait domain scores; the FFBF version
adds 2 forensic domains after them (see below). Following the APA
scoring key (Step 3), each domain score is the mean of the average scores of
its 3 primary facets (the map is stored in pid_domains). The BF version
scores its 5 domains directly from its items, and adds a total score. By
default (missing = "apa") all versions apply the APA missing-data and
proration rule; use missing = "available" or missing = "complete" for
the traditional rowMeans() behaviors. For per-scale reliability estimates
(Cronbach's alpha, McDonald's omega), use reliability_pid5().
The PID5BF+M
version = "BFPM" scores the PID5BF+M of Bach et al. (2020), a 36-item
form with 6 domains: the 5 PID-5 trait domains and Anankastia. Every item
is a PID-5 item, and none is reverse-keyed. The output
is 18 facets of 2 items each, then 6 domains, in the order of the form's
key: Negative affectivity, Detachment, Antagonism, Disinhibition,
Anankastia and Psychoticism. Each domain score is the mean of its 3 facet
scores (the map is stored in pid_bfpm_domains). The 15 facets the form
shares with the PID-5 keep their PID-5 column names. The three Anankastia
facets are perfectionism, rigidity and orderliness. All six of their
items are PID-5 Rigid Perfectionism items, but these facets are not parts
of rigidPerfectionism, which this version does not score.
Scores are item means on the 0 to 3 scale, as for the other versions. The
form's published key sums the 2 items of a facet and averages the facet
sums for a domain. On complete data, the key's facet sum is
2 * pid_<facet> and its domain score is 2 * pid_<domain>.
No missing-data rule is published for this form. Under the default
missing = "apa", the 25% rule applied to a 2-item facet means that any
missing item makes the facet NA, and an NA facet makes its domain
NA. So with whole-number responses "apa" gives the same output as
"complete" here. (The APA rule rounds each scale's sum, so responses
with decimals can differ.) Under missing = "available", a facet can be
scored from one item and a domain from one or two of its facets.
The PID-5 Informant Form
version = "IRF" scores the PID-5 Informant Form (PID-5-IRF; Markon et
al., 2013), the APA's 218-item form on which an informant rates the person
receiving care. Its output is the FULL version's: the same 25 facets and 5
domains, with the same column names and domain map (pid_domains). The
form has no counterpart to self-report items 96 and 177, so its
Anxiousness facet has 8 items and its Suspiciousness facet 6. Informant
item n is self-report item n through 95, n + 1 through 175, and n + 2
after that; pid_items$IRF holds the mapping and pid_items$TextIRF the
informant wording.
Fourteen items are reverse-scored: 7, 30, 35, 58, 87, 90, 96, 97, 130, 141, 154, 163, 208 and 213, the items the key's Facet Table marks R. The key's Step 1 also lists items 98 and 176, which the Facet Table does not mark and whose wording is not reversed; the package does not reverse them.
The key prints its proration step as "round up to the nearest whole
number". The package applies the nearest-whole-number rule of every other
APA PID-5 key, with a prorated half rounded away from zero (see
missing). For a non-negative prorated raw score, the choice matters
only under missing = "apa", for a facet with at least one but no more
than 25% of its items unanswered whose prorated raw score has a
fractional part strictly between 0 and one half. There the package's
facet score is 1/n lower than a ceiling would give, for a facet of n
items. Under a negative srange a negative prorated raw score can also
differ from a ceiling at other fractions.
Informant scores have the full form's column names, and nothing in the
output records the version. Do not pass them to norm_pid5() or
plot_pid5() as version = "FULL": those use self-report norms, and the
informant norms (Markon et al., 2024, Tables A–10 and A–11) are not in
pid_norms. validity_pid5() has no informant validity scales.
The PID-5 Forensic Faceted Brief Form
version = "FFBF" scores the PID-5 Forensic Faceted Brief Form
(PID-5-FFBF; Niemeyer et al., 2022), an adaptation of the 100-item faceted
short form for people in prison, with a self-report and an informant
version. The form was validated in German. The English text in
pid_ffbf_items is the authors' English version, and the study
validated only the German version (p. 40). Items they did not adapt keep
the APA PID-5 wording. Many items are rewritten for prisoners, and the
authors numbered the form afresh, so its items are not the SF's: matched by number, 98 of the
100 SF items fall in a different facet. Facet k, in alphabetical
order, holds items k, k + 25, k + 50 and k + 75. Items 12 and 26 are
reverse-scored.
The output is 25 facets, named and ordered as the SF's, then 7 domains: the 5 APA domains of pid_domains and the two domains of the paper's four-factor solution that are not APA domains, Disinhibited Aggression (Emotional Lability, Hostility, Impulsivity) and Insecurity (Separation Insecurity, Anxiousness, Perceptual Dysregulation). The paper's four-factor Antagonism and Detachment have the facets of the APA domains of the same names, so they are not repeated. pid_ffbf_domains holds the map. The four-factor structure comes from one exploratory study of 199 male prisoners, and the authors leave open whether Insecurity is needed (Niemeyer et al., 2022, p. 39). The seven domains share facets, so they are not independent scores.
Missing data. The paper prints no missing-data rule. Under
missing = "apa" the package applies the full-form APA rule, as it does
for the SF: a facet with 1 of its 4 items missing is prorated and
rounded, a facet with 2 or more missing is NA, and a domain with an
NA facet is NA. The authors' published analysis code scores
differently. It takes the unrounded mean of the answered items for a
facet with 1 item missing, and it scores a domain as the mean of its 12
items when up to 3 of them are missing, wherever they fall. With complete
data the two rules agree. With missing items a facet can differ by up to
1/12 (for example 1.75 here against 1.67 for answers 0, 2 and 3), and a
domain can be NA here where the code gives a value. The paper's
descriptive statistics were computed under the code's rule. No missing
mode reproduces it.
Informant reports. Informant data are scored with the same version.
The paper averaged the responses of two informants item by item before
scoring (p. 33), and the authors' code uses one informant's response
where the other is missing; do that step first, for example with
rowMeans(cbind(x1, x2), na.rm = TRUE) for each item, then set an item
that both informants skipped (NaN from that call) to NA. Averaged responses
can be halves, and they score like any other values. Under
missing = "apa" the proration step rounds them too: a facet with one
item missing and answers 0.5, 1 and 1 scores 0.75, where
missing = "available" gives 0.833. One informant's responses score
directly.
norm_pid5(), plot_pid5() and validity_pid5() do not take the FFBF,
because no FFBF norms or validity keys are published. The FFBF facet and
APA domain columns carry the SF's names, so norm_pid5() converts them
as version = "SF" with no version warning and plot_pid5() plots the
result; do not do that, as it compares them with SF self-report norms
from another population.
The PID-5 child forms
version = "FULL" scores the APA's 220-item PID-5 child form for ages 11
to 17, and version = "BF" scores its 25-item PID-5-BF child form
(Krueger et al., 2013). The child forms print the adult forms' items in
the same order, and their keys reverse the same items and assign them to
the same facets and domains. So no separate version is needed, and data
collected with
generate_docx_pid5child(), generate_qualtrics_pid5child() or
generate_redcap_pid5child() (or their pid5bfchild counterparts) score
as adult data do. pid_norms holds no child norms, so norm_pid5() and
plot_pid5() would compare child scores with norms from another
population. The child forms print no validity scales, and no source on
this package's shelf gives validity cut scores for them, so the cut
scores validity_pid5() applies are not established for child data.
The PID-5-BF total score
version = "BF" returns a total column after its 5 domains. Markon et al.
(2024, p. 23) define it as the item-level mean over all 25 items, not
the mean of the 5 domain means: the total "can be computed by averaging the
overall score by the total number of items in the measure (i.e., 25)". With
five equal-sized domains the two definitions coincide on complete data and
differ only when items are missing, where the published rule above governs.
The total is scored like any other scale, so missing applies to it at the
25-item level. Under missing = "apa" that means it is NA when more than
a quarter of the 25 items are unanswered (7 or more) and prorated otherwise,
independently of the domains. Because a 5-item domain is dropped at 2
unanswered items while the total tolerates 6, a total can be reported
alongside one or more NA domains (at most 3 of the 5; blanking all five
requires 10 unanswered items, which blanks the total as well). This is the
published rule applied as written, not an oversight.
The FULL, SF, IRF, FFBF and BFPM versions have no total score: the PID-5 book defines one only for the brief form, and the PID5BF+M, PID-5-IRF and PID-5-FFBF sources define none.
Errors. With append = TRUE, a column of data whose name this call
would also produce is an error rather than an overwrite or a duplicated
column: the message names every colliding column. Re-run with
append = FALSE to return only the new columns, or drop the colliding
columns from data first. The condition is classed
hitop_append_collision, so a caller can catch this refusal by name.
An item column that cannot be read as numbers (see items) is an error
of class hitop_nonnumeric_items, raised before the collision check.
References
Krueger, R. F., Derringer, J., Markon, K. E., Watson, D., & Skodol, A. E. (2012). Initial construction of a maladaptive personality trait model and inventory for DSM-5. Psychological Medicine, 42, 1879-1890. doi:10.1017/s0033291711002674
Anderson, J. L., Sellbom, M., & Salekin, R. T. (2016). Utility of the Personality Inventory for DSM-5-Brief Form (PID-5-BF) in the measurement of maladaptive personality and psychopathology. Assessment, 25(5), 596–607. doi:10.1177/1073191116676889
Markon, K. E., Fossati, A., Somma, A., & Krueger, R. F. (2024).
Understanding the Personality Inventory for DSM-5 (PID-5). American
Psychiatric Association Publishing. The source for the PID-5-BF total
score's definition (p. 23) and for the normative tables in pid_norms.
Maples, J. L., Carter, N. T., Few, L. R., Crego, C., Gore, W. L., Samuel, D. B., Williamson, R. L., Lynam, D. R., Widiger, T. A., Markon, K. E., Krueger, R. F., & Miller, J. D. (2015). Testing whether the DSM-5 personality disorder trait model can be measured with a reduced set of items: An item response theory investigation of the personality inventory for DSM-5. Psychological Assessment, 27(4), 1195–1210. doi:10.1037/pas0000120
Bach, B., Kerber, A., Aluja, A., Bastiaens, T., Keeley, J. W., Claes, L., Fossati, A., Gutierrez, F., Oliveira, S. E. S., Pires, R., Riegel, K. D., Rolland, J.-P., Roskam, I., Sellbom, M., Somma, A., Spanemberg, L., Strus, W., Thimm, J. C., Wright, A. G. C., & Zimmermann, J. (2020). International assessment of DSM-5 and ICD-11 personality disorder traits: Toward a common nosology in DSM-5.1. Psychopathology, 53(3-4), 179-188. doi:10.1159/000507589 The source of the PID5BF+M.
Markon, K. E., Quilty, L. C., Bagby, R. M., & Krueger, R. F. (2013). The development and psychometric properties of an informant-report form of the Personality Inventory for DSM-5 (PID-5). Assessment, 20(3), 370-383. doi:10.1177/1073191113486513
Markon, K. E., Quilty, L. C., Bagby, R. M., & Krueger, R. F.
(2013). The Personality Inventory for DSM-5—Informant Form
(PID-5-IRF)—Adult. American Psychiatric Association. The scoring key for
version = "IRF".
Niemeyer, L. M., Grosz, M. P., Zimmermann, J., & Back, M. D. (2022). Assessing maladaptive personality in the forensic context: Development and validation of the Personality Inventory for DSM-5 Forensic Faceted Brief Form (PID-5-FFBF). Journal of Personality Assessment, 104(1), 30-43. doi:10.1080/00223891.2021.1923522 The source of the PID-5-FFBF, its items (supplement Table S3) and its domains.
Krueger, R. F., Derringer, J., Markon, K. E., Watson, D., &
Skodol, A. E. (2013). The Personality Inventory for DSM-5 (PID-5)—Child
Age 11–17 and The Personality Inventory for DSM-5—Brief Form
(PID-5-BF)—Child Age 11–17. American Psychiatric Association. The child
forms that version = "FULL" and version = "BF" also score.
Examples
# Score the full PID-5 (25 facets + 5 domains) from the simulated data
score_pid5(sim_pid5, items = 1:220, version = "FULL", append = FALSE)
#> # A tibble: 100 × 30
#> pid_anhedonia pid_suspiciousness pid_riskTaking pid_impulsivity
#> <dbl> <dbl> <dbl> <dbl>
#> 1 1.25 1.71 1.36 2.33
#> 2 1.38 1.57 1.43 2
#> 3 1.88 1 1.29 1.83
#> 4 1.25 2.43 1.21 1.5
#> 5 1.12 1.57 1.64 2.5
#> 6 2.12 1 1.79 1.83
#> 7 1.38 1.14 1.86 1.17
#> 8 1.5 1.71 1.86 0.667
#> 9 1.12 1.14 1.86 1.67
#> 10 1.38 1.86 2.07 2
#> # ℹ 90 more rows
#> # ℹ 26 more variables: pid_eccentricity <dbl>, pid_distractibility <dbl>,
#> # pid_restrictedAffectivity <dbl>, pid_submissiveness <dbl>,
#> # pid_withdrawal <dbl>, pid_callousness <dbl>,
#> # pid_separationInsecurity <dbl>, pid_attentionSeeking <dbl>,
#> # pid_emotionalLability <dbl>, pid_depressivity <dbl>, pid_hostility <dbl>,
#> # pid_irresponsibility <dbl>, pid_rigidPerfectionism <dbl>, …
# Short form, using the item column names instead of positions
score_pid5(sim_pid5sf, items = sprintf("pid5sf_%03d", 1:100), version = "SF",
append = FALSE)
#> # A tibble: 100 × 30
#> pid_suspiciousness pid_impulsivity pid_submissiveness pid_callousness
#> <dbl> <dbl> <dbl> <dbl>
#> 1 1.5 1.5 1 2.25
#> 2 2 1.25 1 2
#> 3 0.5 1.5 1.25 1.5
#> 4 2 1 2 1.25
#> 5 2.75 0.75 1 1.25
#> 6 0.75 1.5 2.75 1.5
#> 7 0.75 0 1.75 1
#> 8 0.5 0.75 1 2.25
#> 9 2.25 1.75 2 1.5
#> 10 1 1.25 1.75 1.5
#> # ℹ 90 more rows
#> # ℹ 26 more variables: pid_anhedonia <dbl>, pid_eccentricity <dbl>,
#> # pid_hostility <dbl>, pid_riskTaking <dbl>, pid_grandiosity <dbl>,
#> # pid_perceptualDysregulation <dbl>, pid_separationInsecurity <dbl>,
#> # pid_deceitfulness <dbl>, pid_perseveration <dbl>,
#> # pid_attentionSeeking <dbl>, pid_anxiousness <dbl>, pid_depressivity <dbl>,
#> # pid_withdrawal <dbl>, pid_restrictedAffectivity <dbl>, …
# Brief form (5 domains + the total) with standard errors. `calc_se` is
# deprecated, so this call warns; the PID-5 has no interval function to
# replace it with.
score_pid5(sim_pid5bf, items = 1:25, version = "BF", calc_se = TRUE,
append = FALSE)
#> Warning: The `calc_se` argument is deprecated.
#> ℹ It, and the `_se` columns it adds, will be removed in a future release.
#> ℹ This package has no interval function for the PID-5; for measurement
#> precision see `reliability_pid5()`.
#> # A tibble: 100 × 12
#> pid_disinhibition pid_detachment pid_psychoticism pid_negativeAffectivity
#> <dbl> <dbl> <dbl> <dbl>
#> 1 1.8 1.6 2 1.8
#> 2 2.2 2.2 2.2 1.4
#> 3 2.4 1.2 1.8 1.6
#> 4 2.4 2.2 0.8 0.8
#> 5 2.2 1.2 1.4 2.8
#> 6 1.8 0.6 2.2 1.2
#> 7 1 2 1.6 1.4
#> 8 1.4 1.8 1.2 1.8
#> 9 1.6 0.8 2.2 0.8
#> 10 1.2 1.8 1.4 0.6
#> # ℹ 90 more rows
#> # ℹ 8 more variables: pid_antagonism <dbl>, pid_total <dbl>,
#> # pid_disinhibition_se <dbl>, pid_detachment_se <dbl>,
#> # pid_psychoticism_se <dbl>, pid_negativeAffectivity_se <dbl>,
#> # pid_antagonism_se <dbl>, pid_total_se <dbl>
# PID5BF+M (18 facets + 6 domains). No BF+M dataset ships, but every BF+M
# item is a PID-5 item, so take its 36 items from the full-form data in
# BF+M order.
bfpm_rows <- pid_items[!is.na(pid_items$BFPM), ]
bfpm_rows <- bfpm_rows[order(bfpm_rows$BFPM), ]
sim_bfpm <- sim_pid5[sprintf("pid5_%03d", bfpm_rows$FULL)]
score_pid5(sim_bfpm, items = 1:36, version = "BFPM", append = FALSE)
#> # A tibble: 100 × 24
#> pid_emotionalLability pid_anxiousness pid_separationInsecurity pid_withdrawal
#> <dbl> <dbl> <dbl> <dbl>
#> 1 1.5 1.5 1.5 2
#> 2 2 0.5 0 2.5
#> 3 1.5 0 2 1
#> 4 1 1 0.5 2
#> 5 1 0.5 1.5 0.5
#> 6 1.5 1.5 2 0.5
#> 7 2 1.5 1 1
#> 8 2.5 1.5 1 1
#> 9 2 1.5 3 1.5
#> 10 1.5 1 2 2
#> # ℹ 90 more rows
#> # ℹ 20 more variables: pid_anhedonia <dbl>, pid_intimacyAvoidance <dbl>,
#> # pid_manipulativeness <dbl>, pid_deceitfulness <dbl>, pid_grandiosity <dbl>,
#> # pid_irresponsibility <dbl>, pid_impulsivity <dbl>,
#> # pid_distractibility <dbl>, pid_perfectionism <dbl>, pid_rigidity <dbl>,
#> # pid_orderliness <dbl>, pid_unusualBeliefsExperiences <dbl>,
#> # pid_eccentricity <dbl>, pid_perceptualDysregulation <dbl>, …
# PID-5 Informant Form (25 facets + 5 domains). No informant dataset ships;
# for illustration, take the 218 full-form items the informant form maps to.
irf_rows <- pid_items[!is.na(pid_items$IRF), ]
sim_irf <- sim_pid5[sprintf("pid5_%03d", irf_rows$FULL)]
score_pid5(sim_irf, items = 1:218, version = "IRF", append = FALSE)
#> # A tibble: 100 × 30
#> pid_anhedonia pid_suspiciousness pid_riskTaking pid_impulsivity
#> <dbl> <dbl> <dbl> <dbl>
#> 1 1.25 2 1.36 2.33
#> 2 1.38 1.67 1.43 2
#> 3 1.88 0.833 1.29 1.83
#> 4 1.25 2.67 1.21 1.5
#> 5 1.12 1.83 1.64 2.5
#> 6 2.12 1.17 1.79 1.83
#> 7 1.38 1.17 1.86 1.17
#> 8 1.5 1.5 1.86 0.667
#> 9 1.12 1.17 1.86 1.67
#> 10 1.38 2 2.07 2
#> # ℹ 90 more rows
#> # ℹ 26 more variables: pid_eccentricity <dbl>, pid_distractibility <dbl>,
#> # pid_restrictedAffectivity <dbl>, pid_submissiveness <dbl>,
#> # pid_withdrawal <dbl>, pid_callousness <dbl>,
#> # pid_separationInsecurity <dbl>, pid_attentionSeeking <dbl>,
#> # pid_emotionalLability <dbl>, pid_depressivity <dbl>, pid_hostility <dbl>,
#> # pid_irresponsibility <dbl>, pid_rigidPerfectionism <dbl>, …
# PID-5-FFBF (25 facets + 7 domains). No FFBF dataset ships; for
# illustration, simulate answers to its 100 items.
set.seed(1)
sim_ffbf <- as.data.frame(matrix(sample(0:3, 500, replace = TRUE), 5, 100))
score_pid5(sim_ffbf, items = 1:100, version = "FFBF", append = FALSE)
#> # A tibble: 5 × 32
#> pid_suspiciousness pid_impulsivity pid_submissiveness pid_callousness
#> <dbl> <dbl> <dbl> <dbl>
#> 1 2.5 1 1.5 2.25
#> 2 1.25 0.75 1.5 0.75
#> 3 0.75 1.75 1.5 1.5
#> 4 1.75 1.5 1 2
#> 5 1.5 1.5 0.5 0.75
#> # ℹ 28 more variables: pid_anhedonia <dbl>, pid_eccentricity <dbl>,
#> # pid_hostility <dbl>, pid_riskTaking <dbl>, pid_grandiosity <dbl>,
#> # pid_perceptualDysregulation <dbl>, pid_separationInsecurity <dbl>,
#> # pid_deceitfulness <dbl>, pid_perseveration <dbl>,
#> # pid_attentionSeeking <dbl>, pid_anxiousness <dbl>, pid_depressivity <dbl>,
#> # pid_withdrawal <dbl>, pid_restrictedAffectivity <dbl>,
#> # pid_intimacyAvoidance <dbl>, pid_rigidPerfectionism <dbl>, …