For a simple linear regression model with $n$ observations, the leverage (hat value) of the $i$-th observation is given by $h_{ii} = \frac{1}{n} + \frac{(x_i - \bar{x})^2}{\sum (x_j - \bar{x})^2}$. If an observation has an independent variable value equal to the sample mean ($x_i = \bar{x}$), what is its leverage value?