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

Chapters 2 & 3: Personality Methods & Assessment Flashcards

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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
Experimental Method
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
26
Correlational Method
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
27
Scatter Plot
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
28
Correlation Coefficient
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
29
Objective Test
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
Factor Analysis
a statistical technique for finding clusters of related traits, tests, or items
31
p-Level
in statistical data analysis, the probability that the obtained correlation or difference between experimental conditions would be expected by chance
32
Type I Error
in research, the mistake of thinking that one variable has an effect on, or relationship with, another variable, when it really does not
33
Type II Error
in research, the mistake of thinking that one variable does not have an effect on or relationship with another, when it really does
34
Effect Size
a number that reflects the degree to which one variable affects, or is related to, another variable
35
Binomial Effect Size Display (BESD)
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
Replication
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
Publication
the tendency of scientific journals preferentially to publish studies with strong results
38
Questionable Research Practices (QRP's)
research practices that, while not exactly deceptive, can increase the chances of obtaining the result the researcher desires
39
p-Hacking
analyzing data in various ways until one finds the desired results
40
Open Science
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
What is Funder's Second Law?
there are no perfect indicators of personality; there are only clues, and clues are always ambiguous the clues may be wrong
42
What is Funder's Third Law?
something beats nothing, two times out of three need evidence, not just a gut feeling
43
What are the advantages of S-Data?
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
What are the disadvantages of S-Data?
bias error too simple and easy (overuse)
45
What is face validity?
the degree to which an assessment instrument appears to measure what it is intended to measure
46
What factors reduce reliability?
random variation or mistakes, result in measurement error
47
What factors reduce validity?
directed, pointing to one particular result, results in bias
48
What are the advantages of I-Data?
real-world bias large amount of data common sense definitional truth causal force
49
What are the disadvantages of I-Data?
limited information lack of access to private experience bias error
50
What are the advantages of L-Data?
not prone to bias intrinsic importance psychological relevance
51
What are the disadvantages of L-Data?
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
What are the advantages of B-Data?
wide range of contexts appearance of subjectivity
53
What are the disadvantages of B-Data?
difficult and expensive uncertain interpretation
54
How is S data differentiated from B data?
S data: asking people about themselves B data: performance based assessments, people demonstrate behaviors, not report them
55
What is reliability?
consistency in measurement
56
What is test-retest reliability?
consistency over time only for traits, not for states
57
What is inter-rater reliability?
consistency among observers
58
What is internal consistency?
consistency across items all measuring the same thing
59
What is validity?
the degree to which a measurement actually measures what is it supposed to
60
What is construct validity?
establish that our measure is related to the construct we want to measure
61
What is criterion validity?
outcome or behavior
62
What is convergent validity?
someone should score high on extraversion and low on introversion
63
What is discriminant validity?
make sure we are measuring intelligence, not just how much the child talks
64
What is Funder's Fourth Law?
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
What are the four conditions of rational test construction?
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
What are experimental methods?
manipulated at least one variable can demonstrate causality determine whether one variable can affect another not possible (or ethical) with certain variables
67
What are correlational methods?
measured variables can't demonstrate causality shows how often or how much variables are related, typically
68
What is a representative design?
generalizability across people generalizability across methods/designs consistency in patterns
69
What is the p level?
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
What are the problems with significance testing?
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
What is the effect size?
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
How can we make research more dependable?
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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