  We introduce a bootstrap procedure to test the hypothesis $H_o$ that $K+1$
variances are homogeneous. The procedure uses a variance-based statistic, and
is derived from a normal-theory test for equality of variances. The test
equivalently expressed the hypothesis as $H_o: \mathbf{\eta}=(
\eta_1,\ldots,\eta_{K+1})^T=\mathbf{0}$, where $\eta_i$'s are log contrasts of
the population variances. A box-type acceptance region is constructed to test
the hypothesis $H_o$. Simulation results indicated that our method is generally
superior to the Shoemaker and Levene tests, and the bootstrapped version of
Levene test in controlling the Type I and Type II errors.
