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Unit 2 Flashcards

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
STR & WK of Alt./Parallel R.
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
26
Internal Consistency Reliability
Inter-corr. of items in same test -Tests w/ heterogeneous items usually have low INT Consistency Rel.
27
INT consistency Rel. Method
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
28
Split-half
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?
29
Spearman-Brown Correction FOrmula
Finds rel. of a full test w/ a split-half corr. adj. UP
30
Split-half Cont.
Many ways to do a split-half, how done effects outcome
31
Coefficient Alpha
M of all possible split-half corr. of a test -No correction needed
32
STR of HIGH INT Consistency
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
Inter-rater (I-R) Rel. Method
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
I-R Reliability Cont.
Low I-R Rel. maybe from unstable characteristics -Difference in sampling can DEC alt./parallel forms R
35
Factors that Affect Rel.
-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
Understanding Rel. Coefficients
0.8-0.9+ is considered acceptable rel. -0.8 R = 80% true difference, 0.2 = 20% random error
37
Item Response Theory (IRF)
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
Info Function
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
Standard Error of Measurement (SEM)
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
Standard Error of the Difference
Error btwn 2 scores helps understand profile of results
41
Validity
How well a test measures what its intended to -How trustful is conclusion from test results? -Info accumulates overtime w/ clinical & rsch observations
42
The relationship btwn Rel. & Val.
R. DEC, Val. DEC -+ e R. INC, ≠ V. INC Cannot est. V w/out R.
43
Are there Valid tests?
No -V. is population specific -V needs to be documented for: *Certain pop. *Certain purpose *Certain setting -Name doesn't matter, evidence does
44
Categories of Validity
Each has some overlap -Content V. -Criterion V. -Construct V. Evidence should be gathered at multiple points
45
Face V.
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
Content V.
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
Construct Underrep.
Test neglects to include key topics -EX: If Uber driver didn't have license
48
Construct Irrelevant Diff.
When test measures something irrelevant -EX: Math test Qs reading comprehension
49
Criterion-Related-V (C-R-V)
How well a test measures IRL qualities/bhvr -Criterion: Standard for eval. obt scores -Has 2 subtypes: Concurrent & Predictive
50
False Positive & False Negative
F+: Test shows person has a quality they don't F-: Test shows person doesn't have a quality they do have
51
ConCURRENT C-R-V
How well results reflect someone's standing on a current IRL dimension -EX: Dr.'s opinion & depression score
52
Predictive C-R-V
How well results predict someone's standing on a IRL dimension in the future -EX: GPA
53
Shortcut to gather info & save time, $, & effort
Using a valid test
54
Validity Coefficient
Corr. coefficient indicating STR of relationships btwn test scores & criterion measure -Rarely above 0.6 -EX: Corr. btwn depression & Dr.'s rate
55
Criterion Contamination
Scorer for criterion also knows test scores -Artificial corr. elevation -EX: Prof. knows student's GRE score & assigns grades -Confirmation bias
56
Standard e of Estimate (SEE)
Stat indicates degree of e for estimated scores -Confidence interval of e -High corr. btwn test & criterion, DEC SEE
57
Decision Theory
% of "hits" / true + & true - AND % of "misses" false + & false - -Acceptable ratio dependent on nature of decision to be made
58
Construct
Unobservable, underlying, hypothesized trait of interest -A lot of psych subjects involve these
59
Construct Validity
The extent to which a test adequately measures a theoretical construct/trait -EX: What does watermelon sugar high?
60
Sources for evidence Construct Val.
Seven: -Test homogeneity -Appropriate Developmental Changes -Theory-consistent Intervention Effects -Theory Consistent Group Difference -Convergence Evidence -Discriminant (Divergent) Evidence -Factor Analysis
61
Test Homogeneity
INT consistency - How well a single trait is measured w/ test
62
Appropriate Dev. Changes
Expected changes in scores w/ age -Principal of conservation -EX: Grade lvl & reading score
63
Theory-Consistent Intervention Effects
Changes in scores in pre/post-test following known effective intervention -EX: Known therapeutic intervention OR Bhvr changing w/ experience
64
Convergence Evidence
STR corr. btwn scores on new & older est. test on similar construct -"og" log, hog BUT "int" hint, pint
65
Discriminant (Divergent) Evidence
Scores should theoretically be unrelated/have no corr. should show why diff. -EX: Dr. Skelly & Hawley bringing subs to the "all cookie" party
66
Factor Analysis
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
Sensitivity
Accurately IDing patients w/ a particular disorder
68
Specificity
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
Extra Val. Concerns
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
Afunctional Perspective
Are actions of testing beneficial? -Giving reading tests but not having a way to help
71
Test Utility
Practical concern for use of test - Is it useful?

Psych Assessment (4 decks)

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