Developing a Measure: scales, validity and reliability

Types of Measures

1. Observational2. Physiological and Neuroscientific3. Self-report

--majority of social & behavioral science research

Self-report measures People’s replies to written

questionnaires or interviews Can measure:

▪ thoughts (cognitive self-reports)▪ feelings (affective self-reports)▪ actions (behavioral self-reports)

Self-Report

Self-reported momentary emotions: Positive and Negative Affect

Schedule (PANAS)

(Watson, Clark & Tellegen,1988) Indicate the extent you feel this way right now: enthusiastic

Not at all enthusiastic 1 2 3 4 5

Very enthusiastic

Indicate the extent you feel this way right now: upset

Not at all upset 1 2 3 4 5 Very upset

Scales of Measurement

Nominal

Hot = 1

Warm = 3

Cold = 2

Ordinal

1st Place Sample

2nd Place Sample

3rd Place Sample4th Place Sample

5th Place Sample

Thing beingmeasured

Interval Interval Ratio

Scales of MeasurementFour Types

Distinction between scales is due to the meaning of numbers

1. Nominal Scale—numbers assigned are only labels.

2. Ordinal Scale—a rank ordering.

3. Interval Scale—each number equidistant from the

next, but no zero point (majority of measures).

4. Ratio Scale—each number is equidistant and there is

a true zero point.

Scales of Measurement

Type of Scale Determines Statistics and Power

Statistics PowerNominal Chi-square LowOrdinal Rank-order tests ModerateInterval Parametric tests

(F-tests, t-tests)High

Ratio Parametric tests and math operations

High

Attributes of Good Measures

Valid: measure assesses the construct it is intended to and is not influenced by other factors

Reliable: the consistency of a measure, does it provide the same result repeatedly.

Reliability and Validity

Reliable but not Valid Dependable measure, but doesn’t measure what

it should

Example: Arm length to measure self-esteem.

Valid but not Reliable Measures what it should,

but not dependably

Example: Stone as a measure of weight in Great Britain.

Reliability vs. Validity Visual

Central dot = construct we are seeking to measure

Reliability Assessments 1 Test-Retest Reliability

Measure administered at two points in time to assess consistency. Works best for things that do not change over time (e.g., intelligence).

Internal Consistency ReliabilityJudgments of consistency of results across

items in the same test administration session. 1. Intercorrelation: Chronbach’s α (> .65 is preferred)2. Split halves reliability

Types of Validity

Content ValidityDoes the measure represent the range of possible

items the it should cover based on the meaning of the measure.

Predictive Validitymeasure predicts criterion measures that are

assessed at a later time. Ex: Does aptitude assessment predict later success?

Construct ValidityDoes the measure actually tap into intended construct?

Developing Items for a New Measure

Guided spontaneous response from individuals in sample population (thought listings, essay questions…)

Face valid items: develop items that appear to measure your construct.

Pilot test a larger set of items and choose those that are more reliable & valid.

Reversed coded items indicate whether participants are paying attention.

Use common response scale types

Likert Scale: To what extent do you agree with the following statement… (0 to 9, strongly disagree-strongly agree)

Semantic Differential:What is your response to (insert person, object, place, issue)? (-5 to +5, good-bad, like-dislike, warm-cold)

Pitfalls of New Measures

The measure exists already in the literature

Restriction of range: responses either at high or low end of scale (skew).

Can you trust responses? Social desirability, demand characteristics & satisficing.

Simple things I have learned.1. Develop subjective and objective versions of a

new scale Example: Contact with Blacks scale:

Objective: % of your neighborhood growing upSubjective: No Blacks—a lot of Blacks

2. Using 5+ items worded similarly provides greatly increased reliability and likelihood of success.

3. Human targets are rarely evaluated below the midpoint of the scale, so use more scale points (9 instead of 5 points).

**Most Important** If you have a larger study ready and a great idea for a new scale comes up, build something and give it a shot!

A Few Types of Non-scale measures

Response time measures Physiological measures Neuroscience: fMRI and other brain

imaging Indirect measures: projective tests, etc. Facial and other behavior coding schemes

(verbal/nonverbal) Cognitive measures: (memory,

perception…) Task performance: academic, physical… Game theory: prisoner’s dilemma…

SPSS: Reliability

Chronbach’s α: AnalyzeScaleReliability Analysis

Pull over all scale items Click Statistics, select inter-item correlations

OK

Try Van Camp, Barden & Sloan (2010) data file. Centrality1-Centrality8. Compare to manuscript.

Many other reliability analyses involve correlations (test-retest, split halves) or probabilities (inter-rater reliability).

Case Processing Summary

N %

Cases Valid 109 86.5

Excludeda 17 13.5

Total 126 100.0

a. Listwise deletion based on all variables in the

procedure.

Reliability Statistics

Cronbach's

Alpha

Cronbach's

Alpha Based on

Standardized

Items N of Items

.706 .743 8

Inter-Item Correlation Matrix

centrality1rev centrality2 centrality3 centrality4rev centrality5 centrality6 centrality7 centrality8rev

centrality1rev 1.000 .244 .069 .297 .082 .170 .148 .208

centrality2 .244 1.000 .298 .323 .509 .411 .588 .031

centrality3 .069 .298 1.000 .206 .398 .337 .398 .042

centrality4rev .297 .323 .206 1.000 .213 .160 .350 .284

centrality5 .082 .509 .398 .213 1.000 .589 .637 -.063

centrality6 .170 .411 .337 .160 .589 1.000 .475 .075

centrality7 .148 .588 .398 .350 .637 .475 1.000 -.041

centrality8rev .208 .031 .042 .284 -.063 .075 -.041 1.000

SPSS-Output

END

Advanced Scale Development Techniques

Factor Analysis: determines factor structure of measures (does your measure assess one construct or multiple constructs? Is your proposed construct coherent?)

Multi-trait Multi-method Matrix: using combination of existing measures and manipulations to establish convergent/ divergent validity with measure.

Reliability Assessments 2

Inter-rater ReliabilityIndependent judges score participant

responses and the % of agreement is assessed to indicate reliability. Used particularly for measures requiring coding (video coding, spontaneous responses…).