4.6: Validity
- Page ID
- 124463
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)- Define validity.
- List and describe the different types of validity.
What is Validity?
Types of Validity
1. Face Validity
Face validity refers to whether a measure seems reasonable "on its face." When you look at the questions asked, do they intuitively make sense as a way to measure the concept? For example, asking people how often they attend religious services is a logical way to measure "religiosity." Conversely, trying to measure "employee morale" by counting how many books are checked out of an office library lacks face validity because the two things do not seem connected.
2. Content Validity
Content validity assesses whether a measure covers the entire range of the concept. A concept often has multiple parts, and a valid measure must include all of them. For example, if you define "satisfaction with restaurant service" as including the quality of the food, the friendliness of the staff, and the atmosphere of the room, your survey must ask about all three. If you only ask about the food, your measure lacks content validity because it ignores important parts of the concept.
3. Convergent and Discriminant Validity
These two forms of validity look at how a measure relates to other concepts:
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Convergent Validity: This checks if your measure aligns with other ways of looking at the same concept. If you use two different surveys to measure "organizational knowledge," the results from both should point in the same direction.
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Discriminant Validity: This checks if your measure is distinct from things it shouldn't be related to. If you are measuring "organizational knowledge," your results should not be exactly the same as a measure of "organizational performance." If they are, you aren't really measuring knowledge; you are just measuring performance by another name.
4. Criterion-Related Validity
This examines how well a measure matches up with real-world results or other established standards. It includes two forms:
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Predictive Validity: Does the measure successfully predict a future result? For example, do results from a college entrance exam accurately predict how well a student will perform in their future college courses?
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Concurrent Validity: Does the measure align with other standards measured at the same time? For example, if a student performs well on a test for one math class, they should reasonably be expected to do well on a test for another math class taken at the same time, because both are testing the same underlying skill.
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Validity: The accuracy of a measurement—ensuring the researcher is actually measuring what they claim to measure.
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Face Validity: Whether the measure seems reasonable "on its face" or intuitive.
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Content Validity: Whether the measure covers the entire range or all dimensions of a concept.
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Convergent Validity: Whether the measure aligns with other ways of looking at the same concept.
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Discriminant Validity: Whether the measure is distinct from concepts it should not be related to.
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Criterion-Related Validity: How well a measure aligns with real-world results or established standards (predictive and concurrent).