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Planned Missing Data Design 2: Two-Method Measurement

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Part of the book series: Statistics for Social and Behavioral Sciences ((SSBS))

Abstract

In the early stages of developing measures of any construct, the primary objective is to develop a reasonable measure of the construct. Thus, it is common for the early measures of a construct to be a measure that is readily available, often involving a simple self-report, or a relatively noninvasive physical, physiological, or biological approach to measurement. However, the early measures often have construct validity problems that become obvious only as the science of measurement matures for that construct. Overtime, researchers develop better measures of the construct, that is, measures with considerably improved construct validity.

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Notes

  1. 1.

    We do have some question about whether the universal acceptance of a measure as being better than, say, self-reports, is sufficient to mean that such measures will work well in TMM models. A good counter example is that the uniaxial accelerometer has long been virtually universally accepted as an appropriate validator for self-reported PA; but as we have argued in this chapter, this practice may not be justified.

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Graham, J.W., Shevock, A.E. (2012). Planned Missing Data Design 2: Two-Method Measurement. In: Missing Data. Statistics for Social and Behavioral Sciences. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4018-5_13

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