This article presents a didactic discussion of a multilevel covariance structure modeling approach to estimation of lowest level mediation effect indexes in two-level studies. The procedure is useful when addressing questions about relations among total and indirect effects between variables of interest while accounting for the hierarchical structure of analyzed data. The discussed method also permits interval estimation and hypothesis tests with respect to related quantities of relevance when evaluating mediated effects with clustered data, and is illustrated on a two-level data set. (Contains 1 figure, 1 table and 1 footnote. Appended are: (1) Syntax File for Two-Level Mediational Analysis; and (2) SPSS Command File for Point and Interval Estimation of the Ratio Direct to Indirect Effect (r1) and Proportion Mediated Effect (r2).)