
When a Measurement Procedure yields consistent scores when the phenomenon being measured is not changing.

Degree to which scores are free of
“measurement error”

Consistency of measurement

•
The extent to which measures indicate what they are intended to measure.
•
The match between the conceptual definition and the operational definition.

RELATIONSHIP BETWEEN
RELIABILITY AND VALIDITY
•
Necessary but not sufficient
•
Reliability is a prerequisite for measurement validity
• One needs reliability, but it’s not enough

•
Measuring height with reliable bathroom scale
• Measuring “aggression” with observer agreement by observing a kid hitting a Bobo doll

• 1. Stability Reliability
• 2. Equivalence Reliability

•
Test-retest
•
SAME TEST – DIFFERENT TIMES
•
Testing phenomenon at two different times;
•
The degree to which the two measurements of “Sam Ting,” using same measure, are related to one another
•
Only works if phenomenon is unchanging

•
Administering same questionnaire at 2 different times
•
Re-examining client before deciding on intervention strategy.
• Running “trial” twice (e.. g. errors in tennis serving)

Notes on Stability Reliability
• When ratings are by an observer rather than the subjects themselves, this is called
Intraobserver Reliability or Intrarater
Reliability.
• Answers about the past are less reliable when they are very specific, because the questions may exceed the subjects’ capacity to remember accurately.

1.
Inter-item (split ½)
2.
Parallel forms
[Different types of measures]
3.
Interobserver Agreement
-Is every observer scoring the same ?

1. Inter-item Reliability
•
(Internal consistency) : The association of answers to a set of questions designed to measure the same concept.

Note on Inter-item Validity
• The stronger the association among individual items and the more items included, the higher the reliability of an index
• Cronbach’s alpha is a statistic commonly used to measure inter-item reliability
• Cronbach’s alpha is based on the average of all the possible correlations of all the split 1/2s of a set of questions on a questionnaire

2. Parallel forms of Reliability
• Split ½ (inter-item)
•
Different types of measures
•
Interobserver Reliability
–
Is everyone measuring the same thing ?
•
Different measures – same time

•
Correspondence between measures made by different observers.

Note for Stat Students Only
•
The text inadvertently describes a 3 rd type of reliability that we’re not concerned with in this class: ‘goodness of fit’ about a slope line. It’s sometimes referred to as random measurement error.
•
Save this for Grad School =)

Note on Reliability
•
For Statistics people, the following quote refers to ‘ goodness of fit
’ around a slope line due to measurement error .
Secondary Definition of Reliability from a previous slide
“…or that the measured scores changes in direct correspondence to actual changes in the phenomenon”

•
1 . Content Validity
–
Face Validity
–
Sampling Validity (content validity)
•
2. Empirical Validity
–
Concurrent Validity
–
Predictive Validity
•
3 . Construct Validity

• confidence gained from careful inspection of a concept to see if it’s appropriate “on its face;”
•
In our [collective] intersubjective, informed judgment, have we measured what we want to measure?
•
(N.B. use of good judgment)

Example of Face Validity
• Rosenberg’s self esteem scale questions:

Content validity
• Also called “sampling validity”
• establishes that the measure covers the full range of the concept’s meaning, i.e., covers all dimensions of a concept
•
N.B depends on “good “ judgment

Example of content validity
•
Earlier SES scale in class
•
Authoritarian personality questions from
Walizer & Wienir

•
Actually I think face and content validity are probably Sam Ting

EMPIRICAL Validity
•
Establishes that the results from one measure match those obtained with a more direct or already validated measure of the same phenomenon (the “criterion”)
•
Includes
–
Concurrent
–
Predictive

Concurrent Validity
•
Validity exists when a measure yields scores that are closely related to scores on a criterion measured at the same time
•
Does the new instrument correlate highly with an old measure of the same concept that we assume (judge) to be valid? ( use of
“good” judgment
)

Example of concurrent validity
• Aronson’s doodle measure of achievement motivation.
•
Act vs. SAT

Predictive Validity
•
Exits when a measure is validated by predicting scores on a criterion measured in the future
•
Are future events which we judge to be a result of the concept we’re measuring anticipated [predicted] by the scores we’re attempting to validate
• Use of “good” judgment

Examples of Predictive Validity
• Bronson screening test for “at risk” parenting followed up by interviewing and observing family members and school staff later
•
Sat / ACT scores and later college
“performance” (grades)
• Grades are “judged” to be measured validly

What’s a Construct?
[
NSB
]*
• Multidimensional concept
– SES
–
Industrialization
•
Fuzzy concept / hard to define
–
Ego strength
– Love
• Concept build out of other concepts
– Force=mass * acceleration
* Ya better know these!!!!!

Consider This:
•
If a construct is hard to conceptualize doesn’t it make sense that it’ll be more difficult to operationalize and validate?

Construct validity
•
: established by showing that a measure is
(1) related to a variety of other measures as specified in a theory, used when no clear criterion exists for validation purposes (2) that the operationalization has a set of interrelated items and (3) that the operationalization has not included separate concepts

Construct validity
•
Check the intercorrelation of items used to measure construct judged to be valid
•
Use theory to predict a relationship and use a judged to be valid measure of the other variable then check for relationship
• Demonstrate that your measure isn’t related to judged to be valid measures of un related concepts

Convergent Validity
•
Convergent validity : achieved when one measure of a concept is associated with different types of measures in the same concept (this relies on the same type of logic as measurement triangulation)
•
Measures intercorrelated

Example of questions that
Interrelate
Questions for Companionate…intimacy
•
We get along well
•
We communicate
•
We like the same stuff
•
Our chemistry is good
•
We support each other

Discriminant Validity
•
Discriminant validity : scores on the measure to be validated are compared to scores on measures of different but related concepts and discriminant validity is achieved if the measure to be validated is
NOT strongly associated with the measures of different concepts
•
Measure not related to un related concepts

Questions for Passion
•
I think my partner is HOT
•
My partner turns me on
• When I’m with my partner I just feel the electricity

Using theory
•
Measure of constructs predicts what theory says it should

•
Companionate rel longevity satisfaction