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.