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| bfi   | R Documentation   |
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25 Personality items representing 5 factors
-------------------------------------------

Description
~~~~~~~~~~~

25 personality self report items taken from the International
Personality Item Pool (ipip.ori.org) were included as part of the
Synthetic Aperture Personality Assessment (SAPA) web based personality
assessment project. The data from 2800 subjects are included here as a
demonstration set for scale construction, factor analysis, and Item
Response Theory analysis. Three additional demographic variables (sex,
education, and age) are also included.

Usage
~~~~~

::

    data(bfi)

Format
~~~~~~

A data frame with 2800 observations on the following 28 variables. (The
q numbers are the SAPA item numbers).

``A1``
    Am indifferent to the feelings of others. (q\_146)

``A2``
    Inquire about others' well-being. (q\_1162)

``A3``
    Know how to comfort others. (q\_1206)

``A4``
    Love children. (q\_1364)

``A5``
    Make people feel at ease. (q\_1419)

``C1``
    Am exacting in my work. (q\_124)

``C2``
    Continue until everything is perfect. (q\_530)

``C3``
    Do things according to a plan. (q\_619)

``C4``
    Do things in a half-way manner. (q\_626)

``C5``
    Waste my time. (q\_1949)

``E1``
    Don't talk a lot. (q\_712)

``E2``
    Find it difficult to approach others. (q\_901)

``E3``
    Know how to captivate people. (q\_1205)

``E4``
    Make friends easily. (q\_1410)

``E5``
    Take charge. (q\_1768)

``N1``
    Get angry easily. (q\_952)

``N2``
    Get irritated easily. (q\_974)

``N3``
    Have frequent mood swings. (q\_1099

``N4``
    Often feel blue. (q\_1479)

``N5``
    Panic easily. (q\_1505)

``O1``
    Am full of ideas. (q\_128)

``O2``
    Avoid difficult reading material.(q\_316)

``O3``
    Carry the conversation to a higher level. (q\_492)

``O4``
    Spend time reflecting on things. (q\_1738)

``O5``
    Will not probe deeply into a subject. (q\_1964)

``gender``
    Males = 1, Females =2

``education``
    1 = HS, 2 = finished HS, 3 = some college, 4 = college graduate 5 =
    graduate degree

``age``
    age in years

Details
~~~~~~~

The first 25 items are organized by five putative factors:
Agreeableness, Conscientiousness, Extraversion, Neuroticism, and
Opennness. The scoring key is created using ``make.keys``, the scores
are found using ``score.items``.

These five factors are a useful example of using ``irt.fa`` to do Item
Response Theory based latent factor analysis of the ``polychoric``
correlation matrix. The endorsement plots for each item, as well as the
item information functions reveal that the items differ in their
quality.

The item data were collected using a 6 point response scale: 1 Very
Inaccurate 2 Moderately Inaccurate 3 Slightly Inaccurate 4 Slightly
Accurate 5 Moderately Accurate 6 Very Accurate

as part of the Synthetic Apeture Personality Assessment (SAPA) project.
To see an example of the data collection technique, visit
`http://test.personality-project.org <http://test.personality-project.org>`_.
The items given were sampled from the International Personality Item
Pool of Lewis Goldberg using the sampling technique of SAPA. This is a
sample data set taken from the much larger SAPA data bank.

Source
~~~~~~

The items are from the ipip (Goldberg, 1999). The data are from the SAPA
project (Revelle, Wilt and Rosenthal, 2010) , collected Spring, 2010 (
`http://test.personality-project.org <http://test.personality-project.org>`_).

References
~~~~~~~~~~

Goldberg, L.R. (1999) A broad-bandwidth, public domain, personality
inventory measuring the lower-level facets of several five-factor
models. In Mervielde, I. and Deary, I. and De Fruyt, F. and Ostendorf,
F. (eds) Personality psychology in Europe. 7. Tilburg University Press.
Tilburg, The Netherlands.

Revelle, W., Wilt, J., and Rosenthal, A. (2010) Personality and
Cognition: The Personality-Cognition Link. In Gruszka, A. and Matthews,
G. and Szymura, B. (Eds.) Handbook of Individual Differences in
Cognition: Attention, Memory and Executive Control, Springer.

See Also
~~~~~~~~

``bi.bars`` to show the data by age and gender, ``irt.fa`` for item
factor analysis applying the irt model.

Examples
~~~~~~~~

::

    data(bfi)
    describe(bfi)
     keys.list <- list(Agree=c(-1,2:5),Conscientious=c(6:8,-9,-10),Extraversion=c(-11,-12,13:15),Neuroticism=c(16:20),Openness = c(21,-22,23,24,-25))
     keys <- make.keys(28,keys.list,item.labels=colnames(bfi))
     score.items(keys,bfi)
     scores <- score.items(keys[1:27,],bfi[1:27]) #don't score age 
     scores
     

