PLS SEM on a non-complex model?
Posted: Mon Nov 11, 2019 2:41 am
Hello everyone,
I have been using PLS SEM for 4 years now. I have been writing articles, and the models are usually complex with higher models, mediating/moderating variables, theory development etc. Recently, I've collaborated with a co-author on an agricultural paper and I suggested on the use of PLS SEM rather than SPSS. But I have failed to consider why PLS SEM as it became a habit to use the software each time I write. The agriculture paper is not complex at all. We used PCA to come up with dimensions and from there, used the dimensions to predict the dependent variable. We sent to a journal and one of the feedbacks given was "Why use PLS SEM?". I could not think of any other reasons besides predictive/causal effect reasoning. The sample size of this paper is also large (n = 500). Anyone here could help us on how to tackle this? Thanks.
I have been using PLS SEM for 4 years now. I have been writing articles, and the models are usually complex with higher models, mediating/moderating variables, theory development etc. Recently, I've collaborated with a co-author on an agricultural paper and I suggested on the use of PLS SEM rather than SPSS. But I have failed to consider why PLS SEM as it became a habit to use the software each time I write. The agriculture paper is not complex at all. We used PCA to come up with dimensions and from there, used the dimensions to predict the dependent variable. We sent to a journal and one of the feedbacks given was "Why use PLS SEM?". I could not think of any other reasons besides predictive/causal effect reasoning. The sample size of this paper is also large (n = 500). Anyone here could help us on how to tackle this? Thanks.