Subject to the limitations in the topic Accuracy of the bootstrap, bootstrapping offers the following advantages within Amos: Bootstrapping does not require distributional assumptions (although it does require independent observations). Bootstrapped standard errors are available for most of the statistics produced by Amos (not just for model parameters). Bootstrapping works for any estimation criterion, including Uls and Sls. Bootstrapping works even if the specified model is wrong.