I am working with a very large dataset (total n = 30,000+) of normally distributed measurement data on birds. Sample sizes are such that any and all traditional (e.g., ANOVA) hypothesis tests are statistically significant. Rather than use an information theory approach to model selection I decided to run resampling stats (bootstrap) to generate probabilities of observed values under the null hypothesis.

First, does this approach seem reasonable? Second, can anyone provide any published examples of this application of resampling stats?