What is an example of a Heterotrait Heteromethod correlation?
Heterotrait-Heteromethod Triangles These are correlations that differ in both trait and method. For instance, A1-B2 is . 22 in the example. Generally, because these correlations share neither trait nor method we expect them to be the lowest in the matrix.
What is Convergent validity in psychology?
Convergent validity refers to how closely the new scale is related to other variables and other measures of the same construct. Not only should the construct correlate with related variables but it should not correlate with dissimilar, unrelated ones.
What is concurrent validity and examples?
When we examine concurrent validity, both measures are taken at the same time. For example, sample participants were given the Rice Depression Scale and the Beck Depression Inventory at the same time. When measuring predictive validity, one measurement is given before the other.
Who is the creator of the Multitrait Multimethod Matrix?
What is the Multitrait-Multimethod Matrix? The Multitrait-Multimethod Matrix (hereafter labeled MTMM) is an approach to assessing the construct validity of a set of measures in a study. It was developed in 1959 by Campbell and Fiske (Campbell, D. and Fiske, D. (1959).
When to use a multitrait multimethod correlation matrix?
With measures of different traits by different methods, researchers could generate a correlation matrix—the multitrait-multimethod matrix. The correlation data in the matrix could be used to judge the measurement quality of intended constructs.
How are validity diagonals produced in multitrait matrix?
In Figure 1, three methods produce three validity diagonals: Method 1 by Method 2, Method 2 by Method 3, and Method 1 by Method 3. Third, the heterotrait-monomethod triangles are the light grey areas in Figure 1. These triangles contain bivariate correlations between different constructs applying the same method.
Do you have to use the same matrix for each trait?
In order to obtain the matrix, each trait has to be measured by the same set of methods. This makes it possible to arrange the correlations in such a way that the correlations between different traits measured by the same method can be separated from the correlations between different traits measured by different methods.