Once we have confirmed that the construct measures are reliable and valid, the next step addresses the assessment of the structural model results. This involves examining the model’s predictive capabilities and the relationships between the constructs.

Structural model assessment is for hypotheses testing. It deals with the relationship between latent variables.

• A resampling technique that draws a large number of subsamples from the original data (with replacement) and estimates models for each subsample.

• To determine standard errors of coefficient estimates to assess the coefficient's statistical significance without relying on distributional assumptions.

• The test will give indication whether the relationship is significant ie; statistically different from zero.

Example:

Is there a correlation between IQ & a methodology re-examination result?

IMPORTANT NOTE

The number of bootstrap samples must be larger than the number of valid observations in the original data set but should be higher; generally, 5,000 bootstrap samples are recommended.

FAQ:

Q: What kind of bootstrap confidence interval method should be used?

A: Use the (nonparametric) percentile bootstrapping method. In case of a highly asymmetric parameter distribution (e.g. after graphical inspection of a coefficient’s bootstrap distribution), apply the biascorrected and accelerated bootstrapping (BCa) approach.

Q: How many bootstrap subsamples should be used?

A: The more the better. The number of bootstrap samples must be larger than the number of valid observations in the original data set but should be higher. But as some point out, additional computations only marginally improve the bootstrap distribution and might not justify the additional computations and the time they require. While initial model estimations can draw on a smaller number of bootstrap subsamples (e.g. 1,000), the final analysis should use at least 10,000 subsamples.

Becker, J. M., Cheah, J. H., Gholamzade, R., Ringle, C. M., & Sarstedt, M. (2023). PLS-SEM’s most wanted guidance. International Journal of Contemporary Hospitality Management, 35(1), 321-346.