Hence, reliability and validity are both needed to assure adequate measurement of the constructs of interest.ДЇigure 7.1. Finally, a measure that is reliable but not valid will consist of shots clustered within a narrow range but off from the target. A measure that is valid but not reliable will consist of shots centered on the target but not clustered within a narrow range, but rather scattered around the target. Using the analogy of a shooting target, as shown in Figure 7.1, a multiple-item measure of a construct that is both reliable and valid consists of shots that clustered within a narrow range near the center of the target.

Likewise, a measure can be valid but not reliable if it is measuring the right construct, but not doing so in a consistent manner. Reliability and validity, jointly called the вЂњpsychometric propertiesвЂќ of measurement scales, are the yardsticks against which the adequacy and accuracy of our measurement procedures are evaluated in scientific research.ДЄ measure can be reliable but not valid, if it is measuring something very consistently but is consistently measuring the wrong construct. We also must test these scales to ensure that: (1) these scales indeed measure the unobservable construct that we wanted to measure (i.e., the scales are вЂњvalidвЂќ), and (2) they measure the intended construct consistently and precisely (i.e., the scales are вЂњreliableвЂќ). Hence, it is not adequate just to measure social science constructs using any scale that we prefer. For instance, how do we know whether we are measuring вЂњcompassionвЂќ and not the вЂњempathyвЂќ, since both constructs are somewhat similar in meaning? Or is compassion the same thing as empathy? What makes it more complex is that sometimes these constructs are imaginary concepts (i.e., they donвЂ™t exist in reality), and multi-dimensional (in which case, we have the added problem of identifying their constituent dimensions). The previous chapter examined some of the difficulties with measuring constructs in social science research.

Testing validity and reliability