1 validity – outline 1. definition 2. two different views: traditional 3. two different views:...

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Validity – Outline

1. Definition

2. Two different views: Traditional

3. Two different views: CSEPT

4. Face Validity

5. Content Validity: CSEPT

6. Content Validity: Borsboom

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Validity – Outline

7. Criterion Validity: CSEPTi. Predictive vs. Concurrent

ii. Validity Coefficients

8. Criterion Validity: Borsboom

9. Construct Validity: CSEPTi. Convergent

ii. Discriminant

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Validity – Definition

Validity measures agreement between a test score and the characteristic it is believed to measure

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Validity: CSEPT view

Validity is a property of test score interpretations

Validity exists when actions based on the interpretation are justified given a theoretical basis and social consequences

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Validity: Traditional view

Validity is a property of tests

Does the test measure what you think it measures?

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Note the difference:

Validity exists when actions based on the interpretation are justified given a theoretical basis and social consequences

Does the test measure what you think it measures?

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A problem with the CSEPT view

Who is to say the ‘social consequences’ of test use are good or bad?

According to CSEPT validity is a subjective judgment

In my view, this makes the concept useless: “if you like the result the test gives you, you will consider it valid. If you don’t, you won’t.”

That’s not how scientists think.

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Borsboom et al. (2004)

Borsboom et al reject CSEPT’s view

“Validity… is a very basic concept and was correctly formulated, for instance, by Kelley (1927, p. 14) when he stated that a test is valid if it measures what it purports to measure.” (p. 1061)

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Variations in what you are measuring cause variations in your measurements.

E.g., variations across people in intelligence cause variations in their IQ scores

This is not a correlational model of validity

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You don’t create a test and then do the analysis necessary to establish its validity

Rather, you begin by doing the theoretical work necessary to understand your subject and create a valid test in the first place.

On this view, validity is not a big problem.

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Borsboom et al. vs. CSEPT

Who is right? Each scientist has to

make up his or her own mind on that question

I agree with Borsboom et al.’s arguments.

Other psychologists may disagree.

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The CSEPT view

CSEPT recognizes 3 types of evidence for test validity: Content-related Criterion-related Construct-related

Boundaries not clearly defined

Cronbach (1980): Construct is basic, while Content & Criterion are subtypes.

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Parenthetical Point – Face Validity

Face validity refers to the appearance that a test measures what it is intended to measure.

Face validity has P.R. value – test-takers may have better motivation if the test appears to be a sensible way to measure what it measures.

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Content validity: CSEPT

Content-related evidence considers coverage of the conceptual domain tested.

Important in educational settings

Like face validity, it is determined by logic rather than statistics

Typically assessed by expert judges

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Content validity: CSEPT

Construct-irrelevant variance arises when irrelevant

items are included or when external

factors such as illness influence test scores

requires a judgment about what is truly “external”

Construct under-representation Is domain adequately

covered or are parts of it left out?

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Content validity: Borsboom et al.

Borsboom et al. would say that content validity is not something to be established after the test has been created.

Rather, you build it into your test by having a good theory of what you are testing

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Criterion validity: CSEPT

Criterion-related evidence tells us how well a test score corresponds to a particular criterion measure.

Generally, we want the test score to tell us something about the criterion score.

How well the test does this provides criterion-related evidence

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CSEPT: we could compare undergraduate GPAs to SAT scores to produce evidence of validity of conclusions draw on basis of SAT scores.

Two basic types: Predictive Concurrent

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Predictive validity Test scores used to predict future performance – how good is the prediction?

E.g., SAT is used to predict final undergraduate GPA

SAT – GPA are moderately correlated

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Predictive validity Concurrent validity

Correlation between test scores and criterion when the two are measured at same time.

Test illuminates current performance rather than predicting future performance (e.g., why does patient have a temperature? Why can’t student do math?)

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Criterion validity: Borsboom et al.

“Criterion validity” involves a correlation, of test scores with some criterion such as GPA

That does not establish the test’s validity, only its utility.

E.g., height and weight are correlated, but a test of height is not a test of what bathroom scales measure.

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Criterion validity: Borsboom et al.

SAT is valid because it was developed on the sensible theory that “past academic achievement” is a good guide to “future academic achievement”

Validity is built into the test, not established after the test has been created

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Criterion validity

Note: no point in developing a test if you already have a criterion – unless impracticality or expense makes use of the criterion difficult.

Criterion measure only available in the future?

Criterion too expensive to use?

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Criterion validity

Validity Coefficient Compute correlation (r) between test score and criterion.

r = .30 or .40 would be considered normal.

r > .60 is rare

Note: r varies between -1.0 and +1.0

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Criterion validity

Validity Coefficient r2 gives proportion of variance in criterion explained by test score.

E.g., if rxy = .30, r2 = .09, so 9% of variability in Y “can be explained by variation in X”

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Interpreting validity coefficients

Watch out for: 1. Changes in causal relationships

2. What does criterion mean? Is it valid, reliable?

3. Is subject population for validity study appropriate?

4. Sample size

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Interpreting validity coefficients

Watch out for: 5. Criterion/predictor confusion

6. Range restrictions

7. Do validity study results generalize?

8. Differential predictions

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Construct validity: CSEPT

Problem: for many psychological characteristics of interest there is no agreed-upon “universe” of content and no clear criterion

We cannot assess content or criterion validity for such characteristics

These characteristics involve constructs: something built by mental synthesis.

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Construct validity: CSEPT

Examples of constructs:

Intelligence Love Curiosity Mental health

CSEPT: We obtain evidence of validity by simultaneously defining the construct and developing instruments to measure it.

This is ‘bootstrapping.’

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Bootstrapping construct validity

assemble evidence about what a test “means” – in other words, about the characteristic it is testing.

CSEPT: this process is never finished

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assemble evidence about what a test “means” – in other words, about the characteristic it is testing.

Borsboom: this is part of the process of creating the test in the first place, not something done after the fact

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assemble evidence show relationships

between a test and other tests

CSEPT: none of the other tests is a criterion but the web of relationships tells us what the test means

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assemble evidence show relationships

between a test and other tests

Borsboom: these relationships do not tell us what a test score means (e.g., age is correlated

with annual income but a measure of age is not a measure of annual income).

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assemble evidence show relationships each new relationship

adds meaning to the test

CSEPT: a test’s meaning is gradually clarified over time

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assemble evidence show relationships each new relationship

adds meaning to the test

Borsboom: would say, why all the mystery? The meaning of many tests (e.g., WAIS, academic exams, Piaget’s tests) is clear right from the start

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Construct validity

Example from text: Rubin’s work on Love.

Rubin collected a set of items for a Love scale

He read poetry, novels; he asked people for definitions

created a scale of Love and one of Liking

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CSEPT: Construct validity

Rubin gave scale to many subjects & factor-analyzed results

Love integrates Attachment, Caring, & Intimacy

Liking integrates Adjustment, Maturity, Good Judgment, and Intelligence The two are

independent: you can love someone you don’t like (as song-writers know)

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Rubin’s study of Love

Borsboom et al.: when creating a test, the researcher specifies “the processes that convey the effect of the measured attribute on the test score.”

Rubin laboriously built a theory about what the construct Love means.

Rubin’s process – reading poetry and novels, asking people for definitions – was a good process, so his test has construct validity.

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Campbell & Fiske (1959)

Two types of Construct-related Evidence

Convergent evidence

When a test correlates well with other tests believed to measure the same construct

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Campbell & Fiske (1959)

Two types of Construct-related Evidence

Convergent evidence Discriminant evidence

When a test does not correlate with other tests believed to measure some other construct.

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Convergent validity

Example – Health Index Scores correlated with age, number of symptoms, chronic medical conditions, physiological measures

Treatments designed to improve health should increase Health Index scores. They do.

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Discriminant validity

Low correlations between new test and tests believed to tap unrelated constructs.

Evidence that the new test measures something unique

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Validity & Reliability: CSEPT

CSEPT: No point in trying to establish validity of an unreliable test.

It’s possible to have a reliable test that is not valid (has no meaning).

Logically impossible to produce evidence of validity for an unreliable test.

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Validity & Reliability: Borsboom

Borsboom et al: what does it mean to say that a test is reliable but not valid?

What is it a test of? It isn’t a test at all, just a

collection of items

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Blanton & Jaccard – arbitrary metrics

We observe a behavior in order to learn about the underlying psychological characteristic

A person’s test score represents their standing on that underlying dimension

Such scores form an arbitrary metric

That is, we do not know how the observed scores are related to the true scores on the underlying dimension

6543210

0 1 2 3 4 5 6

Person A Person B

Underlying dimension

Test 1

Test 2

Adapted from Blanton & Jaccard (2006) Figure 1, p. 29

Neutral

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Arbitrary metrics – the IAT

Implicit Association Test (IAT) – claimed to diagnose implicit attitudinal preferences – or racist attitudes

IAT authors say you may have prejudices you don’t know you have.

Are these claims true?

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Task: categorize stimuli using 2 pairs of categories

2 buttons to press, 2 assignments of categories to buttons, used in sequence

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Assignment pattern A Button 1 – press if

stimulus refers to the category White or the category Pleasant

Button 2 – press if stimulus refers to the category Black or the category Unpleasant

Assignment pattern B Button 1 – press if

stimulus refers to the category White or the category Unpleasant

Button 2 – press if stimulus refers to the category Black or the category Pleasant

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IAT authors claim that if responses are faster to Pattern A than to Pattern B, that indicates a “preference” for Whites over Blacks – in other words, a racist attitude

IAT authors also give test-takers feedback about how strong their preferences are, based on how much faster their responses are to Pattern A than to Pattern B

This is inappropriate

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Blanton & Jaccard: The IAT does not tell us about racist attitudes

IAT authors take a dimension which is non-arbitrary when used by physicists – time – and use it in an arbitrary way in psychology

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The function relating the response dimension (time) to the underlying dimension (attitudes) is unknown

Zero on the (Pattern A – Pattern B) difference may not be zero on the underlying attitude preference dimension

There are alternative models of how that (Pattern A – Pattern B) difference could arise

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Review

CSEPT:

1. Validity is a characteristic of evidence, not of tests.

2. Valid evidence supports conclusions drawn using test results

3. Validity is determined by social consequences of test use

Borsboom et al.

1. Validity is not a methodological issue, but a substantive (theoretical) issue

2. A test of an attribute is valid if (a) the attribute exists, and (b) variation in the attribute causes variation in test scores

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Review

CSEPT:4. Validity can be

established in three ways, though boundaries between them are fuzzy:A. Content-related

evidenceB. Criterion-related

evidenceC. Construct-related

evidence

Borsboom et al:3. It’s all the same

validity: a test is valid if it measures what you think it measures

4. Validity is not mysterious

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Review

CSEPT

5. Content-related evidence: do test items represent whole domain of interest?

6. Criterion-related evidence: do test scores relate to a criterion either now (concurrent) or in the future (predictive)?

Borsboom et al.

5. These questions are properly part of the process of creating a test

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Review

CSEPT

6. Construct-related evidence is obtained when we develop a psychological construct and the way to measure it at the same time.

7. A test can be reliable but not valid. A test cannot be valid if not reliable.

Borsboom et al.

6. A test must be valid for a reliability estimate to have any meaning

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Review

Blanton & Jaccard (2006) warn against over-interpretation of scores which are based on an arbitrary metric

For an arbitrary metric, we have no idea how the test scores are actually related to the underlying dimension

1 validity – outline 1. definition 2. two different views: traditional 3. two different views:...

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