Clustering, Bootstrapping, and Multiple Comparisons

Catalog description

Accurate hypothesis testing with focus on best procedures for estimating standard errors and approximating the distribution of test statistics. Central focus on linear models with a wide range of correlation structures, including cluster correlation. Use of the bootstrap to produce finite sample approximations of test statistics. Multiple comparison tests.