| What is the measure? |
| The measures represent defining characteristics that collectively explain the meaning of the construct. |
The measures are manifestations of the latent construct, in that they are determined by it. |
The measures are functions of each other. The psychological constructs refer to groups of behaviors that directly influence each other. |
| Characteristic of the indicators |
| They do not necessarily share a common theme, each indicator can capture a unique aspect of the conceptual domain |
They must be caused by a construct in common and each indicator must capture the essence of the domain of the construction. The indicators are samples of the same conceptual domain. |
There is a need for investigation into the nature of individual indicators, as well as their causal dynamics. |
| Relationship between indicators |
| There are no predictions about the relationships between the indicators, but they should not show a high correlation. |
The theory explicitly states that the indicators must be correlated. |
The question that must be asked is whether two indicators in a network differentiate themselves, if so, they must be aggregated, otherwise they measure two different constructs and must be modeled and understood as distinct nodes within the network. |
| Antecedents and consequences |
| They do not necessarily have the same antecedents and consequences. |
All indicators must have the same antecedents and consequences. |
The relationship can be established between and among indicators. |
| Most prominent criticisms |
Formative measurement models are not identifiable, regardless of the number of measurements used. To achieve identification, the model must be complemented by at least two reflective measures that are caused directly or indirectly by the latent variable (Bollen & Davis, 2009Bollen, K. A., & Davis, W. R. (2009). Causal indicator models: Identification, estimation, and testing. Structural Equation Modeling: A Multidisciplinary Journal, 16(3), 498- 522. https://doi.org/10.1080/10705510903008253
https://doi.org/10.1080/1070551090300825...
; MacCallum & Browne, 1993MacCallum, R. C., & Browne, M. W. (1993). The use of causal indicators in covariance structure models: some practical issues. Psychological Bulletin, 12, 413-429. https://doi.org/10.1037/0033-2909.114.3.533
https://doi.org/10.1037/0033-2909.114.3....
). |
A reflective measurement model is identified as long as it has at least three measures, the indicators they are independent and a scale is defined for the latent variable (Bollen, 1989Bollen, K. A. (1989). Structural equations with latent variables (Vol. 210). John Wiley & Sons. https://doi.org/10.1002/9781118619179
https://doi.org/10.1002/9781118619179...
). The most prominent criticism concerns the need for the underlying cause to fully explain the covariation between the indicators (local independence), something considered implausible. |
A pure form of the network model postulates that the co-occurrence between symptoms is due solely to the causal interactions between the symptoms. Taking into account the various factors that can trigger multiple symptoms at the same time, this is considered unlikely. |
