Hi all,
I'm opening up this thread for those who, like me, didn't get into a biostatistics PhD program and are wondering what to focus on between now and next cycle to increase the likelihood of getting accepted. Obviously, we know that factors like undergraduate GPA, GRE scores, research experience, etc. are considered when an applicant's application is reviewed, but maybe some of us are unsure of which to prioritize.
For me, I have a masters degree in clinical psychology with a concentration in research methods / statistics (statistical coursework from probability and statistical inference to multilevel modeling). Over the past year and a half, I have been completing mathematics prerequisites that were required by biostatistics PhD programs, but I think having Calculus III and Linear Algebra PENDING at the time of application played a significant role in this being an unsuccessful application cycle for me. Note: by May 2019 I will have finished through Linear Algebra and anticipate a 3.95 GPA in my math prereqs.
I was offered admission to the MS in biostatistics at Columbia and MA in biostatistics at Boston University. I am wondering: Is it going to be impossible to get into a biostatistics PhD program without a biostatistics masters degree? I have an exceptional amount of research experience and publications, so it seems that I have three options:
1) Bite the bullet and get a second masters degree (most if not all credits will transfer to a PhD program and I might be able to get my current job to pay for some of this MS degree)
2) Save A LOT of money by foregoing the biostats MS and just get higher GRE scores (I had 157 in both V and Q)
3) Continue taking math coursework to demonstrate math ability (maybe completing coursework just through Linear Algebra is not impressive enough)
Would so greatly appreciate any advice (option 1, 2, 3, or some combination of them?).