Structural equation modelling is key to understanding the internal workings of an ecosystem. I wanted to know if it's possible to build a SEM utilising data such as
1. Soil physical and chemical properties
2. Fungal diversity
3. Agronomic trait.
I have some experiences with AMOS for building simple models. However I don't know if this technique or steps are in the right order.
My work plan is
1. PCA to sort the variables (is it alright to combine all the variables?)
2. CFA to reduce redundancy.
3. Pathway analysis.
One factor that I am worried about is the fact that soil data are quantitative in nature, so different parameters will have different values. Will this effect the model? Or do I have to use the assign a score range. Eg
pH: 0-2(assigned a value of 1)
pH: 2-4 (assigned a value of 2)
And so on.
I would be interested in knowing if there are any suggestions or comments on both techniques and steps. Regards.
Hello Wati,
you should try to take a look into
Shipley, B. (2004). Cause and correlation in biology. A user's guide to path analysis, structural equations and causal inference. Cambridge UK: Cambridge University Press.
Shipley, B. (1997). Exploratory path analysis with applications in ecology and evolution. The American naturalist, 149(6), 1113-1138. doi:10.1086/286041
Furthermore, you are mixing two different approaches how to connect measures with concepts--the reflective / common factor model which is the relevant measurement model underlying EFA and CFA and the composite model which refers to PCA.
In this thread, I posted some relevant key concepts and further papers
https://www.researchgate.net/post/Dear_scholars_how_to_design_a_Structural_Equation_Modeling_surveys
HTH
Holger
Holger Steinmetz thank you for the excellent answer. I shall definitely look ino the suggested materials. Regards
- Badges
- Science topic
- Similar topics
- Biological Science
- Biochemistry
- Biochemical Techniques
- Analytical Chemistry
- pH