how do we describe personality? hans eysenck (d. 9/4/97): inspired by history, especially...
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How do we describe personality?
Hans Eysenck (d. 9/4/97): Inspired by history, especially Hippocrates (460-370 bc) and Galen (129-203 ad)
Phlegmatic
Sanguine
Melancholic
Choleric
High NLow N
High E
Low E
How do we describe personality?
Raymond Cattell (1943; d. 2/2/98) The lexical hypothesis:“All aspects of human personality which are or have been of importance, interest, or utility, have already become recorded in the substance of language”
Allport & Odbert (1936)
17,953 words “distinguish the behavior or one human being from that of another”4,504 words represent “consistent and stable modes” or “determining tendencies”
Cattell (1957)
171 non-redundant/synonymous wordsFactor analysis
Norman (1963)
18,125 words to describe people8,081 words not evaluative, ambiguous, clear, and not physical traits
1,600 familiar words75 clusters
1 2 3 4 5 67
1. I did what had to be done - .10 .75 -.05 .03 .12 .00
2. I learned to live with it - -.02 .52 .61 -.07-.08
3. I tried to get rid of it - .17 .00 .09.15
4. I accepted that it was there - .71 .11.08
5. I tried to see it in a different light - .06-.04
6. I slept more than usual - .59
7. I daydreamed about other things-
Factor: A B C D
1. I did what had to be done .62 .15 .01 -.12
2. I learned to live with it .03 -.08 .49 .08
3. I tried to get rid of it .54 .04 -.20 .16
4. I accepted that it was there .10 .11 .56 .03
5. I tried to see it in a different light .07 .08 .50 .02
6. I slept more than usual -.02 .72 .12 -.13
7. I daydreamed about other things .08 .48 .08 .08
Correlations
1 .217* -.081 -.197* .590** -.102 .544**
.016 .375 .029 .000 .262 .000
123 123 122 123 123 122 122
.217* 1 .415** .451** .008 .546** .028
.016 .000 .000 .929 .000 .758
123 123 122 123 123 122 122
-.081 .415** 1 .535** -.024 .525** .107
.375 .000 .000 .791 .000 .240
122 122 122 122 122 122 122
-.197* .451** .535** 1 -.257** .674** -.143
.029 .000 .000 .004 .000 .117
123 123 122 123 123 122 122
.590** .008 -.024 -.257** 1 -.254** .697**
.000 .929 .791 .004 .005 .000
123 123 122 123 123 122 122
-.102 .546** .525** .674** -.254** 1 -.101
.262 .000 .000 .000 .005 .267
122 122 122 122 122 122 122
.544** .028 .107 -.143 .697** -.101 1
.000 .758 .240 .117 .000 .267
122 122 122 122 122 122 122
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
att1_0
fear1_0
guilt1_0
host1_0
jov1_0
sad1_0
sass1_0
att1_0 fear1_0 guilt1_0 host1_0 jov1_0 sad1_0 sass1_0
Correlation is significant at the 0.05 level (2-tailed).*.
Correlation is significant at the 0.01 level (2-tailed).**.
Correlations
1 .217* -.081 -.197* .590** -.102 .544**
.016 .375 .029 .000 .262 .000
123 123 122 123 123 122 122
.217* 1 .415** .451** .008 .546** .028
.016 .000 .000 .929 .000 .758
123 123 122 123 123 122 122
-.081 .415** 1 .535** -.024 .525** .107
.375 .000 .000 .791 .000 .240
122 122 122 122 122 122 122
-.197* .451** .535** 1 -.257** .674** -.143
.029 .000 .000 .004 .000 .117
123 123 122 123 123 122 122
.590** .008 -.024 -.257** 1 -.254** .697**
.000 .929 .791 .004 .005 .000
123 123 122 123 123 122 122
-.102 .546** .525** .674** -.254** 1 -.101
.262 .000 .000 .000 .005 .267
122 122 122 122 122 122 122
.544** .028 .107 -.143 .697** -.101 1
.000 .758 .240 .117 .000 .267
122 122 122 122 122 122 122
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
att1_0
fear1_0
guilt1_0
host1_0
jov1_0
sad1_0
sass1_0
att1_0 fear1_0 guilt1_0 host1_0 jov1_0 sad1_0 sass1_0
Correlation is significant at the 0.05 level (2-tailed).*.
Correlation is significant at the 0.01 level (2-tailed).**.
Structure Matrix
.841 -.216
.801 -.268
.648 -.014
.639 .068
-.202 .864
-.052 .790
-.071 .698
sad1_0
host1_0
guilt1_0
fear1_0
jov1_0
sass1_0
att1_0
1 2
Factor
Extraction Method: Principal Axis Factoring. Rotation Method: Promax with Kaiser Normalization.
Raymond Cattell (1943; d. 2/2/98)“All aspects of human personality which are or have been of importance, interest, or utility, have already become recorded in the substance of language”
16 factors, including:
Reactive vs. emotionally stableRelaxed vs. tense
Self-assured vs. apprehensiveTolerates disorder vs. perfectionistic
Shy vs. socially boldSerious vs. lively
Forthright vs. privateDominant vs. deferential
How do we describe personality?
Lewis Goldberg: The Big 5
E: The largest number of closely related wordsA: The next largestC: And so onN: And so onO: The smallest number, loosely related words; the worst-defined factor
Costa and McCrae: The Big 3 (plus 2) = The Five-Factor Model
N and E: The most common personality dimensions in personality theoryO: Accounts for existential theories (e.g., self-actualization)
Convinced in 1981 by Big 5 research to include A and C
How do we describe personality?
The Big 5/Five Factors
OCEAN
Other structures?
NEO
CEAN
OCEAN + PV and NV (The Big 7; Tellegen)
O C eX A nE + Honesty/humility (HEXACO; Ashton & Lee)trustworthy, honest, humble, faithful versus greedy, venal, hypocritical, conceited
Hofstee, deRaad, & Goldberg, 1992
How do we describe personality?
Why would we have developed language to describe personality in these five terms?
E: Can I dominate this person?
A: Can I get along with this person?
C: Can I work with this person?
N: Is this person “crazy” or “sane”?
O: Can I teach this person?
How might personality have changed during evolution?