[From Theory of Point Estimation (Lehmann and Casella, 1999, Exercise 6.37)]
Let $P=\{P_\theta:\theta \in \Theta\}$ be a family of probability distributions and assume that $P_\theta$ has pdf $p_\theta$. Let $A$ be a fixed Borel subset of the sample space. For each distribution $P_\theta$, we consider the truncated distribution $P_\theta^\star$ on $A$, i.e., $$ P_\theta^\star (B) = \frac{P_\theta(A\cap B)}{P_\theta(A)} $$ or $$ p^\star_\theta(x)=\frac{p_\theta(x)}{\int_Ap_\theta(y)dy}, x\in A $$ and $0$ otherwise.
Denote $P^\star=\{P^\star_\theta:\theta \in \Theta\}$. Show that
(a) If $T$ is sufficient for $P$, then it is sufficient for $P^\star$
(b) if, in addition, $T$ is complete for $P$ it is also complete for $P^\star$.
I know the same question was asked and given a hint here, but I can't really understand it. Here's how I do (a):
$T$ is sufficient for $P$ iff it is sufficient for $\theta$. Then we have
$$
p(x|\theta) = g(T(x)|\theta)h(x)$$
Let $l(x)=h(x)$ if $x\in A$ and $0$ otherwise, then
$$p^\star(x|\theta) = g(T(x)|\theta) l(x)/c$$ for some constant c, so $p^\star$ is sufficient for $\theta$ and thus for $P$.
Is this proof valid?
Also, it would be really nice if someone could show me how to prove part (b). I am thinking about extending the nonzero $g$ if $T$ is not complete for $P^\star$, but I don't know if that is possible.