Interval estimation of intraclass correlation coefficients in hierarchical designs is discussed within a latent variable modeling framework. A method accomplishing this aim is outlined, which is applicable in two-level studies where participants (or generally lower-order units) are clustered within higher-order units. The procedure can also be used to examine hypotheses about the intraclass correlation coefficient. The approach can be employed with multilevel models containing no predictors, as well with models including at least one higher level predictor. The method is applicable with widely available software, and complements existing literature on evaluation of intraclass correlation coefficients. The discussed approach is illustrated with an empirical example. (Contains 2 figures and 6 footnotes.)