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Psych Assessment > Unit 2 > Flashcards

Unit 2 Flashcards

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1
Q

Correlation Coeficient

A

r ± 1.0
-Sign indicates direction of association
-1.0 = Perfect, 0 = none
-.66 is considered high
-WK: Doesn’t imply causation
-STR: Predicts bhvr

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2
Q

Scatterplot

A

Graphic rep. of corr.
- = Units
-Visual that shows direction & magnitude of corr.
-Helps find outliars

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3
Q

Pearson’s Corr (P’s r)

A

Most used corr. measure
-Used w/ linear corr. & cont. data

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4
Q

Spearman’s Rho

A

Corr. calculated w/ rank-order data
-If rank between variables is similar, STR + corr.

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5
Q

Restricted Rng

A

Scores are tightly clustered
-DEC corr. b/c easiness to move btwn ranks
-DEC variability

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6
Q

Regression

A

“Line of best fit” (regression line) makes predictions using corr. btwn 2 Vs
-Residual (Diff. btwn observed & predicted scores) stays at MIN
-STR of corr. = INC accuracy in predictions, DEC in error
-Observe 1 group and make predictions for another
-Tendency to overestimate relationship

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7
Q

Standard Error of Est.

A

Gives margin info of error when estimating

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8
Q

Coefficient of Determinism (CoD)

A

Coefficient^2

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9
Q

Coefficient of Alienation

A

Measures non-associations btwn Vs
-Square root of 1 - CoD

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10
Q

Shrinkage

A

Amount of DEC observed when
regression is applied to another group

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11
Q

Reliability

A

Consistency of scores
-Degree matters
-Key psychometric feat.

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12
Q

Rel. Coefficient

A

Corr. coefficient indicates rel.

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13
Q

Rel. (R) Tests

A

-Test-restest R.
-Alternate / Parallel forms R.
-Split-half / INT Consistency R.
-Inter-rater R.

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14
Q

Classical Test Theory

A

x = T + e
-x = Obt. score
-T = true score
-e = Random error
EI True score plus random error = obtained score

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15
Q

Systematic (NOT random) Error

A

Error effecting variability

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16
Q

Variance

A

Difference in scores from error & differences in ability

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17
Q

Sources of e (random error) in test scores

A

Test administration
-Test-taker Vs, ENVI & administer-related factors

Test construction
-Items used, item sampling/selection

Test scoring & interpretation

Different test = diff. e

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18
Q

Measurement of e & R

A

e DEC R & repeatability of psych test

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19
Q

Classical Theory

A

Unsystematic measurement e randomly influences
-Measurement e is random
-M e = 0
-True scores and e are not corr., rTe = 0
- e on different tests are not corr., r 12 = 0

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20
Q

Reliability & Classical T

A

True score / Total variance
-Total variance = True score + e variance
-0 (coefficient) = Diff. due to e or chance
-1 = true difference
-0 or 1 = improbable

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21
Q

Test-restest Method

A

1 test given to 2 pple on 2 different occasions
-Shows corr. btwn 1st & 2nd scores for the same test
-H corr = stable test / has test-retest R.
-L corr. = Random e OR No rel., no stability

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22
Q

Things to Consider w/ Test-retest R.

A

Time btwn testing
-Usually days-wks pending on V. Is expected to change
-Rapid changing V = needs sm btwn time, otherwise person changed

How much time is appropriate?
-Ability tests: Time needed to wear off practice & mem. effects
-practice effect = problem for academic & neuropsych settings

Test-retest = best when practice effects don’t affect/minimal

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23
Q

Alt./Parallel Reliability (Coefficient of Equivalence) Method

A

Two versions (V.a, V.b) of test given to 1 group of pple
-Group takes both tests
-V.b can be given immediately or w/ delay after V.a

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24
Q

Alt./Parallel Rel. Cont.

A

Corr. btwn V.a & V.b = Having similar qualities/concepts

Corr. btwn V.a & V.b = concepts diff.
-Maybe caused by item sampling or wording
-Use blueprint to prevent L corr.

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25
Q

STR & WK of Alt./Parallel R.

A

STR:
-DEC cheating/memory effect b/c subjects get different items w/ different form
*Practice effect possible b/c items on different forms are similar

WK:
-INC time, money, & effort to create new version of same test

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26
Q

Internal Consistency Reliability

A

Inter-corr. of items in same test
-Tests w/ heterogeneous items usually have low INT Consistency Rel.

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27
Q

INT consistency Rel. Method

A

1 test given to 1 group on 1 occasion
-Test is split in half, subtotal for each half are corr.
-Best: Odd-even, randomly, matched items
-Worst: 1st & 2nd half

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28
Q

Split-half

A

Yields corr. btwn two half tests, NOT rel. of full test
-Is longer w/ good quality
-More rel. than shorter tests b/c it fully samples bhvr
*Is pic rel. to someone’s appearance VS many pics?

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29
Q

Spearman-Brown Correction FOrmula

A

Finds rel. of a full test w/ a split-half corr. adj. UP

30
Q

Split-half Cont.

A

Many ways to do a split-half, how done effects outcome

31
Q

Coefficient Alpha

A

M of all possible split-half corr. of a test
-No correction needed

32
Q

STR of HIGH INT Consistency

A

Items usually homogenous making scores easy to interpret
-W/ LOW INT Consistency, there is ambiguity & is harder to interpret
-Combine scores from many homogenous subtests to measure complex variables (ex. INT)

33
Q

Inter-rater (I-R) Rel. Method

A

2 Raters/scorers observe & assign scores to 1 group & calculate corr.
HIGH I-R rel. needs:
-Good operational def. of bhvr measured
-In depth training w/ feedback for rater
-Occasional refresher training

34
Q

I-R Reliability Cont.

A

Low I-R Rel. maybe from unstable characteristics
-Difference in sampling can DEC alt./parallel forms R

35
Q

Factors that Affect Rel.

A

-Unstable characteristics affect test-RT R.
-Differences in item sampling of V.a & V.b affect Alt/ Forms Rel.
-Heterogenous items effect INT Consistency Rel.
-Restriction of Rng
*Scores clustered
*Too easy or hard tests

36
Q

Understanding Rel. Coefficients

A

0.8-0.9+ is considered acceptable rel.
-0.8 R = 80% true difference, 0.2 = 20% random error

37
Q

Item Response Theory (IRF)

A

Item characteristic curves (ICC), Relation of a personal trait w/ prob. of correctly scoring on a measure for said trait
-EX: Verbal ability & prob. of passing vocab test
-Look to notebook to understand how to read graph
*A is easiest, D is hardest, B&C moderately hard

38
Q

Info Function

A

To what extent is an item different among people?
-Certain items are different for those LOW on a trait
-Some items made to discriminate those HIGH on a trait
*A in IRT tests those low
*D in IRT tests those high

39
Q

Standard Error of Measurement (SEM)

A

e possible in a test
-Confidence intervals
-e is assumed random
-Rel DEC SEM
-Always a 68% chance score obt is ±1SEM of true score, 68% true is ±1SEM of obt score
-SEM applied to score to interpret it
*SEM = SDxSqR(1-r)

40
Q

Standard Error of the Difference

A

Error btwn 2 scores helps understand profile of results

41
Q

Validity

A

How well a test measures what its intended to
-How trustful is conclusion from test results?
-Info accumulates overtime w/ clinical & rsch observations

42
Q

The relationship btwn Rel. & Val.

A

R. DEC, Val. DEC
-+ e
R. INC, ≠ V. INC
Cannot est. V w/out R.

43
Q

Are there Valid tests?

A

No
-V. is population specific
-V needs to be documented for:
*Certain pop.
*Certain purpose
*Certain setting
-Name doesn’t matter, evidence does

44
Q

Categories of Validity

A

Each has some overlap
-Content V.
-Criterion V.
-Construct V.

Evidence should be gathered at multiple points

45
Q

Face V.

A

How relevant items are to laypersons
-Client understands why Q is being asked
*Type of socks you wear isn’t relevant to job interview at pizza place
-EX: Block design & Rorschach inkblot

46
Q

Content V.

A

How well a test samples what its trying to assess
-Relation btwn sample & Qs to be asked
-Hard to determine w/ poorly defined psych Vs
-Est. w/ agreeance btwn 2 experts rating
-Watch for construct underrep. & Construct Irrelevant Diff.

47
Q

Construct Underrep.

A

Test neglects to include key topics
-EX: If Uber driver didn’t have license

48
Q

Construct Irrelevant Diff.

A

When test measures something irrelevant
-EX: Math test Qs reading comprehension

49
Q

Criterion-Related-V (C-R-V)

A

How well a test measures IRL qualities/bhvr
-Criterion: Standard for eval. obt scores
-Has 2 subtypes: Concurrent & Predictive

50
Q

False Positive & False Negative

A

F+: Test shows person has a quality they don’t
F-: Test shows person doesn’t have a quality they do have

51
Q

ConCURRENT C-R-V

A

How well results reflect someone’s standing on a current IRL dimension
-EX: Dr.’s opinion & depression score

52
Q

Predictive C-R-V

A

How well results predict someone’s standing on a IRL dimension in the future
-EX: GPA

53
Q

Shortcut to gather info & save time, $, & effort

A

Using a valid test

54
Q

Validity Coefficient

A

Corr. coefficient indicating STR of relationships btwn test scores & criterion measure
-Rarely above 0.6
-EX: Corr. btwn depression & Dr.’s rate

55
Q

Criterion Contamination

A

Scorer for criterion also knows test scores
-Artificial corr. elevation
-EX: Prof. knows student’s GRE score & assigns grades
-Confirmation bias

56
Q

Standard e of Estimate (SEE)

A

Stat indicates degree of e for estimated scores
-Confidence interval of e
-High corr. btwn test & criterion, DEC SEE

57
Q

Decision Theory

A

% of “hits” / true + & true - AND % of “misses” false + & false -
-Acceptable ratio dependent on nature of decision to be made

58
Q

Construct

A

Unobservable, underlying, hypothesized trait of interest
-A lot of psych subjects involve these

59
Q

Construct Validity

A

The extent to which a test adequately measures a theoretical construct/trait
-EX: What does watermelon sugar high?

60
Q

Sources for evidence Construct Val.

A

Seven:
-Test homogeneity
-Appropriate Developmental Changes
-Theory-consistent Intervention Effects
-Theory Consistent Group Difference
-Convergence Evidence
-Discriminant (Divergent) Evidence
-Factor Analysis

61
Q

Test Homogeneity

A

INT consistency - How well a single trait is measured w/ test

62
Q

Appropriate Dev. Changes

A

Expected changes in scores w/ age
-Principal of conservation
-EX: Grade lvl & reading score

63
Q

Theory-Consistent Intervention Effects

A

Changes in scores in pre/post-test following known effective intervention
-EX: Known therapeutic intervention OR Bhvr changing w/ experience

64
Q

Convergence Evidence

A

STR corr. btwn scores on new & older est. test on similar construct
-“og” log, hog BUT “int” hint, pint

65
Q

Discriminant (Divergent) Evidence

A

Scores should theoretically be unrelated/have no corr. should show why diff.
-EX: Dr. Skelly & Hawley bringing subs to the “all cookie” party

66
Q

Factor Analysis

A

Data reduction tech. grouping items that have something in common
-Cluster items (Factors) determined stat., interprets factors more subjective
-EX: Crockpot separates meats & veggies

67
Q

Sensitivity

A

Accurately IDing patients w/ a particular disorder

68
Q

Specificity

A

Accurate IDing patients w/out the disorder OR having a different one
-EX: Mini-mental exam screening for dementia in the elderly, cut-off set IDing those w/ disorder and disclude those w/out/have other

69
Q

Extra Val. Concerns

A

Side effects & unintended consequences of testing
-EX: Going to therapy & having a reaction to being given the “batshit crazy” exam
*Value judgement & SOC consequences of tests

70
Q

Afunctional Perspective

A

Are actions of testing beneficial?
-Giving reading tests but not having a way to help

71
Q

Test Utility

A

Practical concern for use of test - Is it useful?

Psych Assessment (4 decks)

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