Computing N-point inverse DFT with N/2-point forward DFT
Just follow your recipe as written


Conjugate your frequency domain vector
Apply DFT on even samples
Apply DFT on odd samples
Recombine the two $N/2$ DFTs to create the $N$ point DFT result
Conjugate the DFT result and divide by N. 


You can swap the last two steps, if you want. 

Keep in mind that there is rarely a good reason to split an $N$ point DFT into two $N/2$ point DFTs. Because of the recombination it's typically more as expensive a single full size DFT. In essence you just take one stage out of the FFT algorithm and compute it manually. The only reason to go there if you have severe memory constraints or cache management issues.

That's different from using a $N/2$ point complex FFTs to compute an $N$ point FFT on real value data. That's generally a considerable savings.