Construct Validity Là Gì

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Construct validity refers lớn the degree to which inferences can legitimately be made from the operationalizations in your study lớn the theoretical constructs on which those operationalizations were based. Like external validity, construct validity is related to lớn generalizing. But, where external validity involves generalizing from your study context to other people, places or times, construct validity involves generalizing from your program or measures khổng lồ the concept of your program or measures. You might think of construct validity as a “labeling” issue. When you implement a program that you Gọi a “Head Start” program, is your label an accurate one? When you measure what you term “self esteem” is that what you were really measuring?

I would like khổng lồ tell two major stories here. The first is the more straightforward one. I’ll discuss several ways of thinking about the idea of construct validity, several metaphors that might provide you with a foundation in the richness of this idea. Then, I’ll discuss the major construct validity threats, the kinds of arguments your critics are likely to lớn raise when you make a clalặng that your program or measure is valid. In most retìm kiếm methods texts, construct validity is presented in the section on measurement. And, it is typically presented as one of many different types of validity (e.g., face validity, predictive validity, concurrent validity) that you might want to lớn be sure your measures have. I don’t see it that way at all. I see construct validity as the overarching quality with all of the other measurement validity labels falling beneath it. And, I don’t see construct validity as limited only lớn measurement. As I’ve already implied, I think it is as much a part of the independent variable – the program or treatment – as it is the dependent variable. So, I’ll try khổng lồ make some sense of the various measurement validity types và try to lớn move sầu you to lớn think instead of the validity of any operationalization as falling within the general category of construct validity, with a variety of subcategories & subtypes.

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The second story I want to tell is more historical in nature. During World War II, the U.S. government involved hundreds (and perhaps thousands) of psychologists and psychology graduate students in the development of a wide array of measures that were relevant to lớn the war effort. They needed personality screening tests for prospective sầu fighter pilots, personnel measures that would enable sensible assignment of people to lớn job skills, psychophysical measures to test reaction times, and so on. After the war, these psychologists needed lớn find gainful employment outside of the military context, và it’s not surprising that many of them moved into lớn testing và measurement in a civilian context.

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During the early 1950s, the American Psychological Association began to lớn become increasingly concerned with the quality or validity of all of the new measures that were being generated & decided lớn convene an effort to lớn mix standards for psychological measures. The first formal articulation of the idea of construct validity came from this effort và was couched under the somewhat grandiose idea of the nomological network. The nomological network provided a theoretical basis for the idea of construct validity, but it didn’t provide practicing researchers with a way to actually establish whether their measures had construct validity. In 1959, an attempt was made to lớn develop a method for assessing construct validity using what is called a multitrait-multimethod matrix, or MTMM for short. In order to argue that your measures had construct validity under the MTMM approach, you had khổng lồ demonstrate that there was both convergent & discriminant validity in your measures. You demonstrated convergent validity when you showed that measures that are theoretically supposed to be highly interrelated are, in practice, highly interrelated. And, you showed discriminant validity when you demonstrated that measures that shouldn’t be related to each other in fact were not.

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While the MTMM did provide a methodology for assessing construct validity, it was a difficult one khổng lồ implement well, especially in applied social research contexts và, in fact, has seldom been formally attempted. When we examine carefully the thinking about construct validity that underlies both the nomological network & the MTMM, one of the key themes we can identify in both is the idea of “pattern.” When we claim that our programs or measures have construct validity, we are essentially claiming that we as researchers understvà how our constructs or theories of the programs and measures operate in theory & we claim that we can provide evidence that they behave in practice the way we think they should. The researcher essentially has a theory of how the programs & measures related to each other (and other theoretical terms), a theoretical pattern if you will. And, the researcher provides evidence through observation that the programs or measures actually behave sầu that way in reality, an observed pattern. When we clalặng construct validity, we’re essentially claiming that our observed pattern – how things operate in reality – corresponds with our theoretical pattern – how we think the world works. I gọi this process pattern matching, and I believe that it is the heart of construct validity. It is clearly an underlying theme in both the nomological network and the MTMM ideas. And, I think that we can develop concrete và feasible methods that enable practicing researchers khổng lồ assess pattern matches – to lớn assess the construct validity of their retìm kiếm. The section on pattern matching lays out my idea of how we might use this approach lớn assess construct validity.