Download presentation

Presentation is loading. Please wait.

Published byMateo Grine Modified over 3 years ago

1
Definitions –Correlation, Reliability, Validity, Measurement error Theories of Reliability Types of Reliability –Standard Error of Measurement Types of Validity Article Exercise Quality of Measures

2
Correlation –reflect direction (+/-) & strength (0 to 1) of the relation between two variables Variance explained –Reflects the strength of relation of two variables Square of correlation Varies from 0 to 1 Definitions

3
Tom Cruise Vince Carter Calista Flockhart Julia Roberts

4
Tom Cruise Vince Carter Calista Flockhart Julia Roberts r =.76 r 2 = 58%

5
Effect of Measurement Error on Correlations

6
r = 1.00 r 2 = 100%

7
r =.98 r 2 = 96%

8
r =.92; r 2 = 85%

9
Reliability Consistency & stability of measurement Reliability is necessary but not sufficient for validity E.g. A measuring tape to is not a valid way to measure weight although the tape reliably measures height and height correlates w/weight Validity Accuracy/meaning of measurement Example: unstructured vs. structured job interviews Definitions

10
Classical Test Theory explains random variation in a person’s scores on a measure Effects of learning, mood, changes in understanding etc. Test score=true score + error Errors have zero mean Errors are uncorrelated with each other Errors are uncorrelated with true score Constant error is part of true score Theories of Reliability

11
Test-retest Consistency across time Parallel forms Consistency across versions Internal Consistency across items Scorer (inter-rater) Consistency across raters/judges Types of Reliability

12
Example: The Satisfaction with Life Scale (SWLS) 1. In most ways my life is close to ideal. 2. The conditions of my life are excellent. 3. I am satisfied with my life. 4. So far I have gotten the important things I want in my life. 5. If I could live my life over, I would change almost nothing. 1234567 Strongly Strongly Disagree Agree

13
Test-retest reliability Correlation of scores on the same measure taken at two different times Time interval assumes no memory/learning effects Parallel-forms Correlation of scores on similar versions of the measure Forms equivalent on mean, stan dev, inter-correlations Can have time interval b/w admin of two forms Types of Reliability

14
I=item P=participant

15
r =.73; r 2 = 50%

16
Test-retest reliability of SWLS Good test-retest reliability Participants have similar scores at Time 1 (beginning of semester) and at Time 2 (end of semester). Retest reliability is useful for constructs assumed to be stable Current mood (e.g., how you feel right now) shows low-retest correlations, but that does not mean that the mood measure is not reliable

17
Internal Consistency Correlation of scores on two halves of the measure Length of measure increases reliability Inter-rater Correlation of raters’ scores E.g., Scores on structured job interview Can also include time interval –e.g., ratings of the worth of jobs across time & across judges Types of Reliability

19
r =.70; r 2 = 49%

20
Internal consistency of SWLS Satisfactory internal consistency. Participants respond similarly to items that are supposed to measure the same variable. Should be.70 or higher Measurement error accounts for half of the variance in SWLS scores.

21
Test-retest Parallel forms Internal Scorer (inter-rater) Types of Reliability

22
SD of scores when a measure is completed several times by the same individual Mostly used in selection contexts Decide which of two individuals are hired Decide whether a test score is significantly higher/lower than a cutoff score Standard Error of Measurement

23
Real correlation between two variables after removing unreliability of each measure Divide observed correlation by product of the square roots of individual reliabilities Note: Selection research only controls for unreliability in criterion bec. we are more interested in the value of the predictor given a perfectly reliable criterion Correction for Attenuation

24
Definitions –Correlation, Reliability, Validity, Measurement error Theories of Reliability Types of Reliability Standard Error of Measurement Types of Validity Quality of Measures

25
Validity Evidence that a measure assesses the construct Reasons for Invalid Measures Different understanding of items Different use of the scale (Response Styles) Intentionally presenting false information (socially desirable responding, other- deception) Unintentionally presenting false information (self-deception)

26
Types of Validity Content Validity Criterion Validity Construct Validity Predictive Validity Concurrent Validity Convergent Validity Discriminant Validity Adapted from Sekaran, 2004

27
Content Validity Extent to which items on the measure are a good representation of the construct e.g., Is your job interview based on what is required for the job? Content validity ratio based on judges’ assessments of a measure’s content e.g., Expert (supervisors, incumbents) rating of job relevance of interview questions Types of Validity

28
Criterion-related Validity Extent to which a new measure relates to another known measure Validity coefficient= Size of relation between the new measure (predictor) and the known measure (criterion) (a.k.a correlation) e.g., do scores on your job interview predict performance evaluation scores? Types of Validity

29
Concurrent Scores on predictor and criterion are collected simultaneously (e.g., police officer study) Distinguishes between participants in sample who are already known to be different from each other Weaknesses Range restriction –Does not include those who were not hired, fired & promoted Differences in test-taking motivation (employees vs. applicants) Experience with job can affect scores on criterion Types of Criterion Validity

30
Predictive Scores on predictor (e.g., selection test) collected some time before scores on criterion (e.g., job performance) Able to differentiate individuals on a criterion assessed in the future Weaknesses Due to management pressures, applicants can be chosen based on scores on predictor (can have range restriction, but this can be corrected) Often, special measures of job performance are developed for validation study Types of Criterion Validity

31
When full range of scores on predictor variable is available –Use unrestricted and restricted standard deviations of predictor variable & the observed correlations b/w predictor & criterion Correction for range restriction

32
Construct Validity Extent to which hypotheses about construct are supported by data 1. Define construct, generate hypotheses about construct’s relation to other constructs 2. Develop comprehensive measure of construct & assess its reliability 3. Examine relationship of measure of construct to other, similar and dissimilar constructs Examples: height & weight; Learning Style Orientation measure; networking; career outcomes Types of Validity (cont’d)

33
Multi-trait multi-method matrix Convergent validity coefficient Absolute size of correlation between different measures of the same construct should be large, significantly diff from zero, Discriminant validity coefficient Relative size of correlations between the same construct measured by different methods compared to Different constructs measured by different methods Different constructs measured by same method (method bias) Establishing Construct Validity

34
O-HSR-HO-WSR-W O-H 1.00 SR-H.981.00 O-W.55.561.00 SR-W.68.69.921.00 Corr b/w Objective (O) & Self- Reports (SR) of Height & Weight

35
Multi-trait multi-method matrix –Different measures of the same construct should be more highly correlated than different measures of different constructs e.g., Perceived career success & promotion vs. networking vs. promotion/salary –Different measures of different constructs should have lowest correlations e.g., Networking vs. promotion/salary Establishing Construct Validity

36
Item Development Study (generate critical incidents) –N=67 –Yes/no responses to statements –Recall of learning events Two types of learning: theoretical, practical Two types of outcomes=success, failure 2 x 2 events per participant 112 items constructed in total Learning Style Orientation Measure

37
Item Development Study (questionnaire) –N=154 –112 items, 5 point likert scale (agree/disagree) 5 factor solution w/factor analyses 54 items Content validity sorting by 8 grad students –Goldberg personality scale Learning Style Orientation Measure

38
Item Development Study Correlations b/w LSO & personality Only 1 sig correlation b/w 5 factors of LSOM! High reliabilities of subscales of LSOM (.81-.91) Construct (not really convergent) validity –r b/w LSOM & personality subscales.42 to -.26. Learning Style Orientation Measure

39
Validation Study –N=350 -193 –LSOM, Personality, old LSI, preferences for instructional & assessment methods Construct validity –r b/w LSOM subscales & old LSI=.01 to.31 –r b/w LSOM & personality subscales=.01 to.55 –Confirmatory factor analysis 5-dimensions confirmed High reliability Learning Style Orientation Measure

40
Validation Study –Incremental validity Additional variance explained (LSOM vs LSI) Learning Style Orientation Measure DVLSOMLSI Subjective assessment.15.01 Interactional instruction.21.04 Informational instruction.06.00

41
Brainstorm constructs to develop measures E.g. Dimensions of CIR professor effectiveness, CIR student effectiveness Choose two constructs that can be measured similarly and be defined clearly Example measures –Self-report (rating scales) –Peer/informant reports –Observation –Archival measures –Trace measures etc etc. In-class Exercise

42
Form two-person groups to Generate items of the 2 different measures for each of the two constructs Appointed person collects all items for both measures for both constructs Compiles & distributes measures to class Class gathers data on both measures & both constructs Class enters data into SPSS format Compute reliabilities,means, correlations In-class Exercise

43
C1 C2 M2 M1 Fill in the correlations

44
Types of Validity Content Validity Criterion Validity Construct Validity Predictive Validity Concurrent Validity Convergent Validity Discriminant Validity Adapted from Sekaran, 2004

Similar presentations

Presentation is loading. Please wait....

OK

Part II Sigma Freud & Descriptive Statistics

Part II Sigma Freud & Descriptive Statistics

© 2018 SlidePlayer.com Inc.

All rights reserved.

Ads by Google

Odp to ppt online converter Ppt on electricity for class 10th math Ppt on earth movements and major landforms in brazil Ppt on communication in india Ppt on life cycle of a butterfly Ppt on db2 mainframes learning Ppt on world book day usa Ppt on personality development for students Ppt on hydrogen fuel cell technology Ppt on online banking system project