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If we do bootstrapping, we can see T-statistic value in Path Coefficient and in Outer Loading tab. What are the differences between them?
Based on literatures I read, T-statistic value in Path Coefficient describes whether the the hypothesis is rejected or accepted. Then, what are described by the T-statistic value in Outer Loading?

Thank in advance.

Exactly what you say: the t value of the outer loading (which usually are very high). But you should rather use the 95% bias-corrected and accelerated (BCa) bootstrap confidence intervals for significance resting (and report those results).

Regards
Christian

I would like to elaborate on this question. When optimizing the model - what is more important: to get more significant path coefficient for IV-LV path or significant indicators for LV? In my model, both are on the border of significance threshold and by increasing the one I decrease the other...
/Elena

First, it depends on what type of measures you have. For reflective measures you always want high and significant loadings of all your indicators to ensure the reliability of your measurement of the constructs.

Second, you want to test the significance of your paths, i.e., find out if one construct has an influence on another as hypothesized by your theory.

Finally, you should not fudge with the significance. Don't optimize your model to get more or better results. Model according to your theoretical considerations and interpret the results.