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15 OCT 7 Wide range of psychology questionnaires traits social attitudes life goals 1 hour of credit Find it here SONA Annual online survey for 1 hour of credit ID: 483967

perspective psychology science research psychology perspective research science behaviour cognitive theme clinical human behavior psychological social credit hour humanistic cultural perspectives physiological

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Slide1

Chapter 2

Personality Assessment,

Measurement, & Research DesignSlide2

Psychometrics & Personality

Individual differences psychology is

closely linked to

psychometrics

Correlation Coefficient (1900)

Factor analysis (1930)

Construct Validity (1950)

Test construction (1960s)Slide3

Primary Measurement Issues

Where

we

get

our information about personality, i.e., our

data sources

.

How we evaluate our

data

quality

.

How we use personality measurements in

data analysis

procedures

to…

Address different research questions with different

research designs

.Slide4

Data Sources:

LOTS of data

L

Life outcome data

O

Observer reports

T

Test data

S

Self-reportsSlide5

The information a person reveals about her/himself in….

Questionnaires

Interviews

Sources of Personality Data

Self-ReportSlide6

Unstructured

“I am ____________”

EXAMPLE:

“20

StatementsTest

I am___________

I am___________I am___________

Sources of Personality Data

Self-ReportSlide7

Sentence Completion Blanks

Washington University Sentence Completion test of Ego-Maturity

(

WUSCTED

)

Jane Loevinger

1) At times she worried about ____________

2) The thing I like about myself is___________

3) I am_________________

Content coding procedure (requires training)Slide8

Structured tests

I am devious.

T F

To be famous. 1 2 3 4 5 6 7

8 9

Types of Response

formats:

Check list

True-False

LikertSlide9

“Likert Scale”

(Likert, 1932)

I am kindhearted. 1 2 3 4 5

To be famous. 1 2 3 4 5 6 7 8 9Slide10

Experience Sampling:

Beepers, cellphones, daily diary

McClelland (1980)

Affiliation study

Compare

TAT

vs Questionnaire

Outcome variable = Freq of affiliating

Result: Both TAT & Ques. predicted

Sources of Personality Data

Self-ReportSlide11

Strength

: Individuals have access to a wealth of information about themselves

Weakness

: Respondents must be honest

Impression management

Self-deception

Sources of Personality Data

Self-ReportSlide12

Del

Paulhus

(UBC)

Socially

Desirable

Responding

SDR

Slide13

Paulhus (1984; 2008

)

SDR is not one thing, but two:

They correspond to 2 kinds of social value:

agentic, communal

Agentic bias

Look competent, powerful, superior

Communal biasLook kind, trustworthy, loyalSlide14

Agency and CommunionSlide15
Slide16

Acquiescence

Yea-saying and Naysaying

Agreeing regardless of content

Disagreeing regardless of content

Solution: Balance wording direction

Controversial because reverse-keyed items sometimes have weaker validity than affirmative worded items. Slide17

Sources of Personality Data

Observer Report Data

Unique access to some data

Data aggregation across observers

Cancel idiosyncratic biases

Improve reliability & validitySlide18

Effect of Aggregation Across Observers

on Heritability Estimates

Reiman et al. (1997) Slide19

Effect of Aggregation Across Observers

on Heritability Estimates

Reiman et al. (1997) Slide20

Sources of Personality Data

Observer Report Data

Types of observers:

Professional (eg IPSR)

+trained to assess reliably and validly

Intimate observers (eg roommate)

+access to natural behavior

+multiple vantage points (spouse, parents)Slide21

Naturalistic vs. Artificial Observation

Immediate vs. Retrospective Observation

Molar vs. Molecular Units of Observation.

Sources of Personality Data

Observer Report DataSlide22

Participants are placed in a standardized testing situation

Procedures are designed to elicit behaviour difficult to observe in everyday life .

Sources of Personality Data

Test DataSlide23

Example: Megargee (1969)

Dominance, gender & leadership

Pre-tested M and F on dominance

Groups=MM, FF, MF, FM (H/L

dom

)

Contrived leadership task

"fix the box " task"assign your own leader"...result:MM: Leader was Dom (75% of time)MF: Leader was M (80% of time) MF: Dom F

chose leader! ( chose M) Slide24

Mechanical Recording Devices

Buss et al. (1980) “Actometer” study

1) Do measures converge? (ratings, actometer data)

2) Is activity-level stable over time?

3) Does actometer predict psychological functioning?

Sources of Personality Data

Test DataSlide25

Physiological Data…

Sources of Personality Data

Test DataSlide26

Functional MRI Slide27

Positron Emission TomographySlide28

Neuroscience of extraversion

Johnson et al. (1999)

PET

9 low (I), 9 high (E)

resting state only

RESULTS

Thalamus I: ↑ Anterior, E: ↑ posterior Insula I:

↑ Anterior, E: ↑ posterior Broca’s Area I >

E

( talking to yourself !!) Slide29

Neuroscience of spiritual feelings

Borg et al. (1999)Slide30

Neuroscience of spiritual feelings

Borg et al. (1999)

Measured “self-transcendence”

Measured serotonin

receptor density

Conclusions

Weak

serotonin binding Weak gating

of sensory stimuli [?]Slide31

Mechanical Recording Devices

Physiological Data

Projective Tests

Sources of Personality Data

Test DataSlide32

RorshchachSlide33

RorschachSlide34

Thematic Apperception Test (TAT)

ap

-perception (

away from +

perception)

"assimilation of perception by prior knowledge"

Created 1930s by Christiana Morgan and Henry Murray

"Tell a story"Analyzed for motivational themes(n=need): nAchieve, nPower, nAffiliation, n-IntimacySlide35
Slide36
Slide37

2000Slide38
Slide39

Rorschach? -No.

TAT? -Yes.Slide40

Information that can be gleaned from the events, activities, and outcomes in a person’s life .

Life-Outcome Data

Sources of Personality DataSlide41

Motor Vehicle Accident Death rate per 10,000

Slide42

Bad-tempered Boys Outcomes

Caspi, Elder, Bem (1989)Slide43

Shy Boys' Outcomes

Caspi, Elder, Bem (1989)Slide44

Evaluating Measure Quality

Reliability

How

trustworthy

is the score?

Test-Retest Reliability

Split Half Reliability

Alternate Forms

Internal Consistency

Coefficient Alpha Slide45

Why so many similar statements?

EPQ Extraversion Scale

30 statements!

Answer: improve reliability

Aggregation

Reduce error variance

Increase Signal/Noise ratio Slide46

Effect of aggregation on Reliability Slide47

Evaluating Data Quality

Reliability

= trustworthiness

Say I use Shoe Size to measure IQ…

Is it a reliable test?

Yes. Measurements of Shoe Size are very stable across time and situations.

Is it a VALID test? … Nope. Validity = meaning of scores. Do the scores truly measure the thing they are supposed to be measuring? Slide48

Types of ValiditySlide49

Face Validity

Face validity = Whether the item content in the measure appears to be logically relevant to the underlying concept being measured. This is not a critical form of validity for a measure, but in some circumstances can be important. Slide50

Content Validity

Content validit

y

= whether the content is

fully representative

of all aspects of the construct being measure. The paranormal beliefs scale above has items to cover all of the primary content distinctions that had been proposed for the concept of “paranormal belief”. Slide51

Convergent Validity

Proof that the scores ARE associated with things they SHOULD be associated with.

Discriminant

Validity

Proof that the scores are NOT associated with things they should NOT be associated with

.

Above are correlations between paranormal beliefs and various other traits. Slide52

Criterion Validity

Does the measure predict something that can be considered a theoretical criterion for the concept--something it

should

predict if the scores were measuring what they are supposed to be measuring?

This example here used

known groups” as criteria:If the paranormal beliefsmeasure is valid, the groupshere should differ in an expected pattern: Relg.fundamentalists should belowest and “spiritualists”should be highest in para-normal beliefs. Slide53

Factorial

Validity

Do the items all

hang together

--do they intercorrelate with each other in the expected manner? In other words, do the items show good “

structure

”? Example: The example on the next page shows results from a factor analysis. The numbers are correlations with two “underlying factors”. All the paranormal items correlate with the same factor, (except P07). All the fundamentalism items correlate with the other factor. These are good results. They suggest the paranormal scale items all hang together as they should, and the fundamentalism items all hang together as they should. Slide54

Factorial Validity

of

a

Paranormal Beliefs Scale

Fac1

Fac2Slide55

Summary of Types of ValiditySlide56

Research Designs

3 Primary Types

1) Case Study

2) Correlational

3) ExperimentalSlide57

Research Designs

Case Studies

SINGLE PERSON

+

More detail, more depth

+

Excellent for developing theory

- Bad for testing theorySlide58

Influential Case Studies

Phineus Gage

(1860)

Anna O

(Freud & Breuer, 1895)

HM

(Henry Molaison, 1953) Mask of Sanity (

Cleckley, 1941)Slide59

Dodge MorganSlide60
Slide61

Morgan sailed alone around the world.

Team of trait researchers did case study of Morgan.

Numerous personality assessments done.

Different measurement approaches were pitted against each other.

Whole issue of Journal of Personality (1997) devoted to Morgan. Slide62

Dodge Morgan Study by Nasby & Reid (1997)

Interpersonal

circumplex

(

Wiggins)

Five

factor Model (Costa & McCrae)Life Story narratives (D. McAdams)

MMPI, Clinical Assessment (J.Butcher)Each perspective provided something unique in understanding Dodge Morgan.Slide63

Research Designs

Correlational: Quantify

covariation

between

things.

Correlation

coefficient: rMagnitude & direction of assoc. (Usually) cannot infer causation from correlation. Slide64

The Correlation Coefficient:

Numerical

index

of covariation

Ranges from:

-

1.0 ..to.. +

1.0“.00” = no association.Q: Which correlation below is the strongest association in the list?A) -.59 B) +.

50 C) -.09 D) +.34 Slide65

Guess the correlation !

Height, weight,

r

= +.

60

Exam 1

, Exam2,

r

= +.

45

Divorce, Neur,

r

= +.

20

Smoking, Lifespan,

r = +.08

Height and Weight

r

.70

+

Neuroticism and Happiness

.30

+

Extrav & Happiness

.50

+

Consc and GPA

.50

-

Aspirin and Heart attack risk

.08

-

Consc and Creativity

.20

-Slide66

3 Common Correlational Relationships:

Additive

, Mediator

,

Moderator Slide67

Additive

Self-Control

Mindfulness

Well-being

r

=.30

r

=.45Slide68

Mediation

Self-Control

Mindfulness

Well-being

( MEDIATOR )

r

=.60

r

=.45

r

= .00Slide69

MAO

Moderation (interaction)

Maltreatment

in childhood

Antisocial

r

=.05

r

=.09

r

=.42Slide70

Fundamentalist

Background

Paranormal Belief

?

Spiritual

BeliefSlide71

Low

High

Spirituality

Paranormal Belief

Religious Fundamentalism

r = .50

r = .00

ModeratorSlide72

Multiple Correlation & RegressionSlide73

Personality of Video GamersSlide74

Causal ModelingSlide75

Factor Analysis

“Seeing the forests instead of the trees”

Finding broad patterns

of covariation among many variables

Partitioning

covariation among many measures into independent sets

Shrinking

a large number of smaller variables into a small number of larger variables.Slide76

Factor a number:

15 = 3 x 5

Factor a matrix of numbers:Slide77

Intercorrelation matrixSlide78

Intercorrelation matrix

2 product matricesSlide79

Intercorrelation matrixSlide80

e.g., We factor analyze a correlation matrix.

Yields

2 product matrices

Eigenvalues, and eigenvectors.

Eigenvectors = “

factor loadings”Slide81

Intercorrelation matrixSlide82

Intercorrelation matrix

2 product matricesSlide83

Factor I

Loadings

Factor II

Body

Mass

Mental

AbilitySlide84

Factor Analysis

Many uses

Discovering trait dimensions

Perceptual sensitivity? Curiosity?

Fantasy-proneness? Liberal Values?

OPENNESS TO EXPERIENCEConstructing taxonomies (e.g., Big Five) Slide85

Data reduction

e.g., Aggregating predictors for regression analyses

Test construction

e.g., Selecting questionnaire items

Factor loadingSlide86

Factor Analysis

Evaluating the

factor structure

of a test

Factorial

validity

”Slide87

Experimental Methods

Typical experiment

Measure a trait

Select Hi vs. Lo on the trait

Put subjects in controlled situation

Manipulate some variable(s)

Measure some outcome(s)

Example…Slide88

Experimental

Methods: Example

Howarth & Eysenck (1988)

How does arousal influence memory?

Depends if STerm or LTerm memory:

“Action Decrement theory”

Example: strong emotion Short-term memory: worsens

Long-term memory: improvesSlide89

Howarth & Eysenck (1988)

High extraversion =

LOW

brain arousal

Low extraversion =

HIGH

brain arousal

If true…E > I short-term recallI > E long-term recall

Slide90

Howarth & Eysenck (1988)

Extraverts

Introverts

Delay Interval

# Words recalledSlide91

“Significance”

Need

to distinguish:

Statistical significance

What is the statistical probability that the result was due to random error?

Practical significance

Does

a result of that magnitude (r = .09) have any real world importance? Slide92

Personality of Video GamersSlide93

Effect Size

Measures of effect size

1. Magnitude

of

experimental effect

Cohen’s

d = (Group1 – Group2) / SD2. CorrelationsCorrelations

are effect sizes.Can convert d to correlation.

Slide94
Slide95

Effect Size

Useful benchmarks:

Large 40+

Medium 25 - 40

Small 15 - 25

Example:

Milgram

(1962) Obedience Study…Slide96

r

=

.40Slide97

Effect Size

Milgram (1962)

effect size was equivalent to r = .40

This is one of the most well-known studies in social psychology.

Trait measures often predict important life outcomes > .40

Traits are indeed real and important. Slide98

Some Effect Sizes in Medicine:

Effect sizes in personality psychology are

not

abysmal.

A growing concern is how

replicable

important research findings are.

Now great interest in systematic

replication research

in psychology.Slide99

SUMMARY

Data sources:

LOTS

Data quality:

Reliability and Validity

Research designs:

Case study

Correlational Experiment