Types of validity

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Conclusion | Internal | Construct | External | Criterion | Content | Face | Threats | See also

In a research project there are several types of validity that may be sought.

Conclusion validity

Conclusion validity occurs when you can conclude that there is a relationship of some kind between the two variables being examined.

This may be positive or negative correlation.

Internal validity

Internal validity occurs when it can be concluded that there is a causal relationship between the variables being studied. A danger is that changes might be caused by other factors.

It is related to the design of the experiment, such as in the use of random assignment of treatments.

Note that this requires that there is already conclusion validity.

Construct validity

Construct validity occurs when the theoretical constructs of cause and effect are true.

This related to how well the experiment is operationalized. A good experiment turns the theory (constructs) into actual things you can measure.

Note that this requires that there is already internal validity.

Convergent validity

Convergent validity occurs where constructs that are expected to relate do so.

Discriminant validity

Discriminant validity occurs where constructs that are expected not to relate do not, such that it is possible to discriminate between these constructs.

Convergence and discrimination are often demonstrated by correlation of the measures used within constructs.

Convergent validity and Discriminant validity together demonstrate construct validity.

Nomological network

Defined by Cronbach and Meehl, this is the set of relationships between constructs and between consequent measures. The relationships between constructs should be reflected in the relationships between measures or observations.

Multitrait-Multimethod Matrix (MTMM)

Defined by Campbell and Fiske, this demonstrates construct validity by using multiple methods (eg. survey, observation, test) to measure the same set of 'traits' and showing correlations in a matrix, where blocks and diagonals have special meaning.

External validity

External validity occurs when the causal relationship discovered can be generalized to other people, times and contexts.

Correct sampling will allow generalization and hence give external validity.

Note that this requires that there is already construct validity.

Criterion-related validity

This examines the ability of the measure to predict a variable that is designated as a criterion.

Criterion-related validity is related to external validity.

Predictive validity

This measures the extent to which a future level of a variable can be predicted from a current measurement.

For example, a political poll intends to measure future voting intent.

Concurrent validity

This measures the relationship between measures made with other, related variables.

For example a measure of employee ability may be expected to relate to a measure of actual performance.

Content validity

Content validity occurs when the experiment provides adequate coverage of the subject being studied. This includes measuring the right things as well as having an adequate sample. Samples should be both large enough and be taken for appropriate target groups.

Content validity is thus related very closely to good experimental design.

Face validity

Face validity occurs where something appears to be valid. This of course depends very much on the judgment of the observer. In any case, it is never sufficient and requires more solid validity to enable acceptable conclusions to be drawn.

Measures often start out with face validity as the researcher selects those which seem likely prove the point.

Threats

Validity as concluded is not always accepted by others and perhaps rightly so. Typical reasons why it may not be accepted include:

• Inappropriate selection of constructs or measures.
• Insufficient data collected to make valid conclusions.
• Measurement done in too few contexts.
• Measurement done with too few measurement variables.
• Inadequate selection of target subjects.
• Complex interaction across constructs.
• Subjects giving biased answers or trying to guess what they should say.
• Experimental method not valid.
• Operation of experiment not rigorous.

See also

Validity, Three izings of research