All the p-values in the structural component of my model are high (not significant)
The p-value in the measurement component are low (significant)
Goodness of fit at this point is at acceptable level. I have not used the modification indices yet.
Is my still model usable?
Only p-value is not important criteria for the model measurement. Model usable depend on another criteria. You may see to measure the Q2, R2 and F2.
1. The Q2 represents a method for assessing the inner model’s predictive relevance (Akter, Ambra, & Ray, 2011). To evaluate the magnitude of the Q2 values represent as a criterion of predictive accuracy (Hair,Ringle, & Sarstedt,2011). Therefore, the smaller the disparity between the predicted and the original values, the larger the Q2 and hence the predictive accuracy of the model (Akter et al., 2011).
2. The effect was measured by following Cohen’s (f2) effect size estimation (Cohen, 1988). Effect size is considered as a small, medium, and large if the values are more than 0.02, 0.15, and 0.35 respectively (Meline & Wang, 2004; Cohen, 1988).
3. The measurement of a model’s analytical accuracy is called R2. It is actually a joint impact of exogenous variables on the endogenous variable. The lowest effect of R2 is 0, and the highest is 1. Hair et al., (2017) explain that the R² values of 0.75, 0.50, and 0.25 on endogenous variables can be called substantial, moderate, and weak respectively.
If the p-values for the structural component are high, suggesting non-significant relationships, while the measurement component shows significance and overall fit is acceptable, your model may still be usable.
Thank you all for your comments. I know high p-values can be justified if the relationship among latent factors are important and known to exist.
Fortunately, after revising my model, the relationship in the structural model is significant now. The measurement model are all significant before anf now both structural and measurement are significant.
To summarize, I made the model simple...removing observed variables I deemed not relevant to my objectives.
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