Wednesday, August 24, 2016

Causal hypotheses:from qualitative to quantitative (SEM style)

The statistical testing of hypotheses about causal sequencing of variables seems to more clearly show nowadays the 2-step process directly stated in Ch. 10 in Conrady & Jouffe, (chapter written with Felix Elwert), process mentioned in my Semnet posting:
1. Causal Identification, followed by
2. Computing the Effect Size.

I found a good example of this approach, within the SEM (Structural Equation Modeling) approach, in a a recent article in Computers in Human Behavior, by Yen & Wu, the sequence is simply: 1. A 'qualitative' (i.e. no numbers!) part: how variables/concepts are expected to 'string themselves' out; and 2. A quantitative part, the post-SEM estimation phase, with numbers attached this time.
1.What one expects:
 2. What one finds (numerically):
Conrady, S. and L. Jouffe, Bayesian Networks and BayesiaLab: 
A Practical Introduction for Researchers. 2015: Bayesia USA: 
free online:
Yen, Y.-S., & Wu, F.-S. (2016). Predicting the adoption of mobile financial services: 
The impacts of perceived mobility and personal habit. Computers in Human Behavior, 
65, 31-42. doi: 

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