Constructs are abstractions that are deliberately created by researchers in order to conceptualize the latent variable, which is correlated with scores on a given measure (although it is not directly observable).
Psychologists such as Samuel Messick (1998) have pushed for a unified view of construct validity "...as an integrated evaluative judgment of the degree to which empirical evidence and theoretical rationales support the adequacy and appropriateness of inferences and actions based on test scores..."[11] While Messick's views are popularized in educational measurement and originated in a career around explaining validity in the context of the testing industry, a definition more in line with foundational psychological research, supported by data-driven empirical studies that emphasize statistical and causal reasoning was given by (Borsboom et al., 2004).
[12] Key to construct validity are the theoretical ideas behind the trait under consideration, i.e. the concepts that organize how aspects of personality, intelligence, etc.
A framework presented by Wieland et al. (2017) highlights that both statistical and judgmental criteria need to be taken under consideration when making scale purification decisions.
He noted that a unified theory was not his own idea, but rather the culmination of debate and discussion within the scientific community over the preceding decades.
This is consistent with the multitrait-multimethod matrix (MTMM) of examining construct validity described in Campbell and Fiske's landmark paper (1959).
Another method is the known-groups technique, which involves administering the measurement instrument to groups expected to differ due to known characteristics.
If there is a significant difference pre-test and post-test, which are analyzed by statistical tests, then this may demonstrate good construct validity.
If this measure has discriminant validity, then constructs that are not supposed to be related positively to general happiness (sadness, depression, despair, etc.)
Lee Cronbach and Paul Meehl (1955)[1] proposed that the development of a nomological net was essential to the measurement of a test's construct validity.
Through the observation of their underlying components psychologists developed new theoretical constructs such as: controlled attention[24] and short term loading.
[25] Creating a nomological net can also make the observation and measurement of existing constructs more efficient by pinpointing errors.
[1] Researchers have found that studying the bumps on the human skull (phrenology) are not indicators of intelligence, but volume of the brain is.
For example, in the nomological network for academic achievement, we would expect observable traits of academic achievement (i.e. GPA, SAT, and ACT scores) to relate to the observable traits for studiousness (hours spent studying, attentiveness in class, detail of notes).
The multitrait-multimethod matrix (MTMM) is an approach to examining construct validity developed by Campbell and Fiske (1959).
[2][26] Apparent construct validity can be misleading due to a range of problems in hypothesis formulation and experimental design.