Heath-Brown's identity states: Let $K \geq 1, z \geq 1.$ Then for any $n < 2 z^K$ we have $$ \Lambda(n) = - \sum_{1 \leq k \leq K} (-1)^k {{K}\choose{k}} \sum_{ \substack{ m_1 \cdots m_k n_1 \cdots n_k = n \\ m_1, \ldots, m_k \leq z }} \mu(m_1) \cdots \mu(m_k) \log n_k. $$
I am trying to better understand this well used identity, and I have a few questions regarding this which I list below. I would greatly appreciate any comments on any of them. Thank you.
1) When is it more advantageous to use Heath-Brown's identity over Vaughan's identity?
2) When applying Heath-Brown's identity, does the terms with $1 \leq k \leq K-1$ are they all type I estimates and the term $k=K$ become type II estimate? (I would appreciate comments on how the identity is used normally...)
3) I have seen in few places that states Heath-Brown's identity is 'more flexible' than Vaughan's identity. What is meant by this?