I'm not able to prove that
$$\frac{\hat{p}_1-\hat{p}_2}{\sqrt{\hat{p}(1-\hat{p})\!\left(\dfrac{1}{n_1}+\dfrac{1}{n_2}\right)}}$$
converges in distribution to $N(0,1)$. Here, $\hat{p}_1$ and $\hat{p}_2$ are independent estimations of the same proportion, $p$, with sample sizes $n_1$ and $n_2$, respectively. Besides, $$\hat{p}=\frac{n_1\hat{p}_1+n_2\hat{p}_2}{n_1+n_2}.$$ I know that $$\frac{\hat{p}_i-p}{\sqrt{\dfrac{p(1-p)}{n_i}}}$$ converges in distribution to $N(0,1)$, for $i=1,2$. My idea was to somehow subtract these two fractions to get the desired property, but convergence in distribution is not guaranteed to be preserved under substraction. I also have that $$\text{E}(\hat{p}_1-\hat{p}_2)=0,\ \text{Var}(\hat{p}_1-\hat{p}_2)=p(1-p)\!\left(\dfrac{1}{n_1}+\dfrac{1}{n_2}\right).$$ However, I am not able to come up with a way to apply the Central Limit Theorem or something similar.
Any help would be appreciated.
PD: sorry if this was asked before, I searched in aproach.xyz and couldn't find anything.