The second generation of statistical modeling
namely Structural Equations Modeling (SEM) distinguishes two measurement models:
reflective and formative latent measurement constructs (Edwards & Bagozzi,
2000).
In reflective construct, the construct is the
cause of the items designed to measure the construct. In other words, the items
can reflect the concept in the construct. However, all the items meant to
reflect the construct are expected to be correlated and, therefore, some of them
can be deleted without affecting the concept in the construct.
As an example, if job satisfaction construct is defined to be measured as a reflective construct, then one
can use items such as
-
I like my job.
-
I’m happy in my work,
-
I am unlikely to want to leave this position.
As illustrated in Figure 1
Figure
1: Reflective Construct
On the other
hand, in the formative construct, the items are the causes of the construct.
Meaningthat, the items meant to measure the construct form the concept in the
construct. These items, however, might not be correlated and, therefore, deleting
any item(s) may cause that some of the construct aspects are ignored.
For example, if job satisfaction construct is conceptualized as a formative construct,
one can use items such as
-
I am satisfied with my pay,
- I have a good boss
-
My work hours are ideal.
- I have many promotion opportunities.
- I enjoy working with my co-workers,….and so on as
illustrated in Figure 2
Figure 2: Formative Construct
As a researcher, the first and most important
step is to clearly define what we are planning to measure and whether our
construct is to be defined reflectively or formatively BEFORE designing a
questionnaire or generating items or questions. Specifically, we have first to
establish a clear conceptual definitions of our constructs and plan how we are
going to measure them.
Reference
Edwards, J. R., & Bagozzi, R. P. (2000). On
the nature and direction of relationships between constructs and measures.
Psychological Methods, 5, 155-174.
