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External validity is the validity of applying the conclusions of a scientific study outside the context of that study. [1] In other words, it is the extent to which the results of a study can generalize or transport to other situations, people, stimuli, and times.
Ecological validity, the ability to generalize study findings to the real world, is a subcategory of external validity. [ 6 ] Another example highlighting the differences between these terms is from an experiment that studied pointing [ 7 ] —a trait originally attributed uniquely to humans—in captive chimpanzees.
External validity is the extent to which the results obtained from a study sample can be generalized "to" some well-specified population of interest, and "across" subpopulations of people, times, contexts, and methods of study. [13]
The validity of a measurement tool (for example, a test in education) is the degree to which the tool measures what it claims to measure. [3] Validity is based on the strength of a collection of different types of evidence (e.g. face validity, construct validity, etc.) described in greater detail below.
Naturalistic observation can also be used to verify external validity, permitting researchers to examine whether study findings generalize to real world scenarios. Naturalistic observation may also be conducted in lieu of structured experiments when implementing an experiment that would be too costly.
Convergent and discriminant validity are ascertained by correlation between similar of different constructs. Content Validity: Subject matter experts evaluate content validity. Criterion Validity is correlation between the test and a criterion variable (or variables) of the construct.
Validity has two distinct fields of application in psychology. The first is test validity (or Construct validity), the degree to which a test measures what it was designed to measure. The second is experimental validity (or External validity), the degree to which a study supports the intended conclusion drawn from the results.
Reliability does not imply validity. That is, a reliable measure that is measuring something consistently is not necessarily measuring what is supposed to be measured. For example, while there are many reliable tests of specific abilities, not all of them would be valid for predicting, say, job performance.