Consider the problem of estimating a $p{ imes}1$ mean vector $ heta(pgeq4)$ under the quadratic loss, based on a sample $X_1$, $X_2$, $cdots$, $X_n$. We find a Lindley type decision rule which shrinks the usual one toward the mean of observations when the underlying distribution is that of a variance mixture of normals and when the norm $parallel;{ heta}-ar{{ heta}}1;{parallel}$ is restricted to a known interval, where $bar{{ heta}}=frac{1}{p};sumlimits_{i=1}^{p}{ heta}_i$ and 1 is the column vector of ones. In this case, we characterize a minimal complete class within the class of Lindley type decision rules. We also characterize the subclass of Lindley type decision rules that dominate the sample mean.