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PSYCH 333 > Chapters 2 & 3: Personality Methods & Assessment > Flashcards

Chapters 2 & 3: Personality Methods & Assessment Flashcards

1
Q

Research

A

exploration of the unknown

finding out something that nobody knew before one discovered it

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2
Q

Funder’s Second Law

A

there are no perfect indicators of personality

there are only clues, and clues as always ambiguous

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3
Q

Funder’s Third Law

A

something beats nothing, two times out of three

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4
Q

S Data

A

self-judgements, or ratings that people provide of their own personality attributes or behavior

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5
Q

Face Validity

A

the degree to which an assessment instrument, such as a questionnaire, on its face appears to measure what it is intended to measure

for example, a face-valid measure of sociability might ask about attendance at parties

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6
Q

Self-Verification

A

the process by which people try to bring others to treat them in a manner that confirms their self-conceptions

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7
Q

I Data

A

informants’ data, or judgements made by knowledgeable informants about general attributes of an individual’s personality

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8
Q

Judgements

A

data that derive, in the final analysis, from someone using his or her common sense and observations to rate personality or behavior

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9
Q

Expectancy Effect

A

the tendency for someone to become the kind of person others expect him or her to be

also known as a self-fulfilling prophecy and behavioral confirmation

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10
Q

Behavioral Confirmation

A

the self-fulfilling prophecy tendency for a person to become the kind of person others expect them to be

also called the expectancy effect

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11
Q

L Data

A

life data, or more-or-less easily verifiable, concrete, real-life outcomes, which are of possible psychological significance

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12
Q

B Data

A

behavioral data, or direct observations of another’s behavior that are translated directly into numerical form

B data can be gathered in natural or contrived (experimental) settings

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13
Q

Reliability

A

in measurement, the tendency of an instrument to provide the same comparative information on repeated occasions

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14
Q

Measurement Error

A

the variation of a number around its true mean due to uncontrolled, essentially random influences

also called error variance

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15
Q

State

A

a temporary psychological event, such as an emotion, thought, or perception

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16
Q

Trait

A

a relatively stable and long-lasting attribute of personality

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17
Q

Aggregation

A

the combining together of different measurements, such as by averaging them

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18
Q

Spearman-Brown Formula

A

in psychometrics, a mathematical formula that predicts the degree to which the reliability of a test can be improved by adding more items

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19
Q

Psychometrics

A

the technology of psychological measurement

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20
Q

Validity

A

the degree to which a measurement actually reflects what it is intended to measure

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21
Q

Construct

A

an idea about a psychological attribute that goes beyond what might be assessed through any particular method of assessment

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22
Q

Construct Validation

A

the strategy of establishing the validity of a measure by comparing it with a wide range of other measures

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23
Q

Generalizability

A

the degree to which a measurement can be found under diverse circumstances, such as time, context, participant population, and so on

in modern psychometrics, this terms includes both reliability and validity

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24
Q

Case Method

A

studying a particular phenomenon or individual in depth both to understand the particular case and to discover general lessons or scientific laws

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25
Q

Experimental Method

A

a research technique that establishes the causal relationship between an independent variable (x) and dependent variable (y) by randomly assigning participants to experimental groups characterized by differing levels of x, and measuring the average behavior (y) that results in each group

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26
Q

Correlational Method

A

a research technique that establishes the relationship (not necessarily causal) between two variables, traditionally denoted x and y, by measuring both variables in a sample of participants

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27
Q

Scatter Plot

A

a diagram that shows the relationship between two variables by displaying points on a two-dimensional plot

usually the two variables are denoted x and y, each point represent a pair of scores, and the x variable is plotted on the horizontal axis while the y variable is plotted on the vertical axis

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28
Q

Correlation Coefficient

A

a number between -1 and +1 that reflects the degree to which one variable, traditionally called y, is a linear function of another, traditionally called x

a negative correlation means that as x goes up, y goes down

a positive correlation means that as x foes up, so does y

a zero correlation means that x and y are unrelated

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29
Q

Objective Test

A

a personality test that consists of a list of questions to be answered by the subject as true or false, yes or no, or along a numeric scale

30
Q

Factor Analysis

A

a statistical technique for finding clusters of related traits, tests, or items

31
Q

p-Level

A

in statistical data analysis, the probability that the obtained correlation or difference between experimental conditions would be expected by chance

32
Q

Type I Error

A

in research, the mistake of thinking that one variable has an effect on, or relationship with, another variable, when it really does not

33
Q

Type II Error

A

in research, the mistake of thinking that one variable does not have an effect on or relationship with another, when it really does

34
Q

Effect Size

A

a number that reflects the degree to which one variable affects, or is related to, another variable

35
Q

Binomial Effect Size Display (BESD)

A

a method for displaying and understanding more clearly the magnitude of an effect reported as a correlation, by translating the value of r into a 2x2 table comparing predicted with obtained results

36
Q

Replication

A

doing a study again to see if the results hold up

replications are especially persuasive when done by different researchers in different labs than the original study

37
Q

Publication

A

the tendency of scientific journals preferentially to publish studies with strong results

38
Q

Questionable Research Practices (QRP’s)

A

research practices that, while not exactly deceptive, can increase the chances of obtaining the result the researcher desires

39
Q

p-Hacking

A

analyzing data in various ways until one finds the desired results

40
Q

Open Science

A

a set of emerging principles intended to improve the transparency of scientific research and that encourage fully reporting all methods and variables used in a study, reporting studies that failed as well as succeeded and sharing data among scientists

41
Q

What is Funder’s Second Law?

A

there are no perfect indicators of personality; there are only clues, and clues are always ambiguous

the clues may be wrong

42
Q

What is Funder’s Third Law?

A

something beats nothing, two times out of three

need evidence, not just a gut feeling

43
Q

What are the advantages of S-Data?

A

high face validity
large amount of data
access to thoughts, feelings, and intentions
definitional truth: self judgements are the only trustworthy truth of things such as self-worth
causal force
simple and easy

44
Q

What are the disadvantages of S-Data?

A

bias
error
too simple and easy (overuse)

45
Q

What is face validity?

A

the degree to which an assessment instrument appears to measure what it is intended to measure

46
Q

What factors reduce reliability?

A

random variation or mistakes, result in measurement error

47
Q

What factors reduce validity?

A

directed, pointing to one particular result, results in bias

48
Q

What are the advantages of I-Data?

A

real-world bias
large amount of data
common sense
definitional truth
causal force

49
Q

What are the disadvantages of I-Data?

A

limited information
lack of access to private experience
bias
error

50
Q

What are the advantages of L-Data?

A

not prone to bias
intrinsic importance
psychological relevance

51
Q

What are the disadvantages of L-Data?

A

multi-determinism: somethings are determined by multiple things not just personality
may lack relevance or be hard to access
records may be incomplete or inaccurate

52
Q

What are the advantages of B-Data?

A

wide range of contexts
appearance of subjectivity

53
Q

What are the disadvantages of B-Data?

A

difficult and expensive
uncertain interpretation

54
Q

How is S data differentiated from B data?

A

S data: asking people about themselves
B data: performance based assessments, people demonstrate behaviors, not report them

55
Q

What is reliability?

A

consistency in measurement

56
Q

What is test-retest reliability?

A

consistency over time

only for traits, not for states

57
Q

What is inter-rater reliability?

A

consistency among observers

58
Q

What is internal consistency?

A

consistency across items all measuring the same thing

59
Q

What is validity?

A

the degree to which a measurement actually measures what is it supposed to

60
Q

What is construct validity?

A

establish that our measure is related to the construct we want to measure

61
Q

What is criterion validity?

A

outcome or behavior

62
Q

What is convergent validity?

A

someone should score high on extraversion and low on introversion

63
Q

What is discriminant validity?

A

make sure we are measuring intelligence, not just how much the child talks

64
Q

What is Funder’s Fourth Law?

A

there are only two kinds of data; terrible data and no data

the potential shortcomings of all kinds of data are precisely what require researchers to always gather every kind they possibly can

65
Q

What are the four conditions of rational test construction?

A

items mean the same thing to the test taker and creator

capability for accurate self-assessment

willingness to make an accurate and undistorted report

items must be valid indicators of what is being measured

66
Q

What are experimental methods?

A

manipulated at least one variable

can demonstrate causality

determine whether one variable can affect another

not possible (or ethical) with certain variables

67
Q

What are correlational methods?

A

measured variables

can’t demonstrate causality

shows how often or how much variables are related, typically

68
Q

What is a representative design?

A

generalizability across people
generalizability across methods/designs
consistency in patterns

69
Q

What is the p level?

A

the probability that the obtained correlation or difference between conditions would be expected by chance

the probability of getting the result found, if the null hypothesis were true

70
Q

What are the problems with significance testing?

A

the logic is difficult to describe (and understand)

the criterion for significance is a arbitrary rule of thumb

nonsignificant results are sometimes misinterpreted to mean “no result” or no relationship or difference

only provides information about the probability of one type of error

71
Q

What is the effect size?

A

strength of association

more meaningful than a significance (p) level

many effect-size measures have been developed

correlation coefficient or Cohen’s d

can be used for predictions

72
Q

How can we make research more dependable?

A

use larger numbers of participants

disclose all methods

share data

report studies that don’t “work”, and explore your data

never regard one study as conclusive proof of anything

PSYCH 333 (10 decks)

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