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Everything posted by cyberwulf

  1. I think your list of schools is pretty reasonable. The top 15 programs are likely out of reach based on your GPA (both undergrad and grad), and it's unlikely that the letters from your supervisors are going to be strong enough to overcome that. However, you have applied work experience, so might be an appealing candidate for more applied programs.
  2. @bayessays Yes, most biostat programs admit 50% or more domestic for funding (training grant) reasons, but the applicant pool is usually >70% international. So the probability of being admitted is lower for international students. Also, this profile isn’t particularly impressive for a domestic biostat applicant in 2021; solid performance at a decent undergrad followed by average performance at a decent MS program is borderline for admission to a top 10 program. (By the way, @LeoStat, please don’t take this the wrong way. Your results could be quite good with strong letters, a
  3. I'm going to be a little bit of a downer here and say that I wouldn't bet on getting into a top 10 biostat program. The applicant pool has gotten insanely deep, and even places outside the top 5 can now afford to accept only the top handful of international students who apply. At our (top 10) program last year, I would estimate that we saw 30-50 international applicants with profiles at least strong as yours; we admitted fewer than 10.
  4. Do you have guaranteed funding at McGill? It can be a challenge to secure that in Canada. Overall, FSU has stronger faculty than McGill, but Erica Moodie at McGill is a star and an obvious choice to work with if you're interested in causal inference.
  5. This is a great answer. Another way of thinking about the distinction is that there is theoretical (= "classical") causal inference, which is about defining and exploring the properties of new estimands and identification approaches, and there is methodological/applied (= "modern") causal inference, which uses the potential outcomes framework and techniques from causal inference to answer specific scientific questions. I tend to think of the former when I think of the term "causal inference"; the latter includes several areas that don't carry the causal name: precision medicine, dynamic treatm
  6. I wouldn't recommend that someone go to an Epidemiology Ph.D. program with the intention of doing methodological research in causal inference. Outside of Harvard (and to a lesser extent UNC), I can't think of any Epi programs with multiple faculty doing causal methods work.
  7. With strong letters you should be able to crack a program ranked in the 15-25 range for biostat programs (think Iowa, Vanderbilt, Florida, etc.) If you can shoulder the cost (or get a scholarship/fellowship), you could definitely get into a top-10 Masters program, where good performance could put you in a position for much better admissions results.
  8. Yeah, don't agonize over it, just politely say that you've chosen to attend a different program.
  9. University of Michigan also (checks notes) has a medical school, and I'm sure plenty of Biostat faculty collaborate with them. And while UM Med (#15 tie on USNews) isn't Penn (#9), it's still very, very good, so there isn't going to be a discernible gap in the quality and availability of medical collaborators. Penn Biostat being under the med school may have a few modest advantages, but it also has some drawbacks. Biostat is a massive academic outlier in the context of the medical school, so there won't be nearly the same kind of cohort experience that you'd get by interacting with students wi
  10. OK, "almost certainly" was probably a little strong. But I would guess that 80-90% of Michigan Biostat MS students who apply to their PhD program end up there.
  11. Harvard doesn't seem to consistently admit their own Masters' students; however, a Harvard MS will get you into a lot of solid Ph.D. programs. Michigan uses its own internal pipeline a lot more for Ph.D. admissions. Though a Michigan MS is well-respected, it won't be viewed quite as highly as the Harvard one if you end up looking to change institutions for your Ph.D. Basically, if you do well at Harvard, you'll have a lot of good options for Ph.D. study, although Harvard itself may not be among them. If you do well at Michigan, you're almost certainly going to stay there for your Ph
  12. Here are some things which come to mind when I think about these programs. Of course, this is based on my observations (and narratives from others) and hence entirely subjective: Harvard: Light coursework, heavy emphasis on research. Can be competitive. Many graduates end up in Harvard-affiliated non-faculty (or contract faculty) positions. Hopkins: Heavy coursework. Fun environment (at least inside the building). Most well-known advisors very "data science"-y. UW: Heavy coursework. Fun student experience. Thin on advisors that don't do variable selection/machine learning. Stud
  13. I see biostat admissions getting more competitive, not because incoming classes are getting smaller (though in some places they may be, somewhat) but because of increased interest in the field of biostatistics due to COVID. Nationally, applications to schools of public health are up about 20%, and while a good chunk of that is in other fields (hello, epidemiology!) there's definitely a spillover effect into biostat. Anecdotally, we're seeing a higher proportion of applications from people whose profile can be summed up as "I'm a smart person who didn't intend to go into biostat but gee that so
  14. Traditionally, UNC/UMich/UMN rarely give funded offers to Masters students (at Michigan, it's only for people who are in the "PhD track"). Duke is definitely a step below those places in terms of prestige, but it's got some good faculty and is located in close proximity to the Research Triangle so is probably a decent bet in terms of landing a good job after you graduate.
  15. You're clearly qualified for an MS stat, but I actually think your problem might be that you're overqualified; in fact, I'm not entirely convinced that most MS Stat programs would even take someone who already has an MS in Quantitative Econ from ISI. You've taken the "core" math stat and probability courses already (at an institution that is known for its excellent statistical training), so all you'd have left to do are a couple of secondary required courses and a handful of electives. Is that really what you want?
  16. If you clicked "Submit" on SOPHAS before 12/1, that is generally considered as having met the deadline. After that point, you just need to make sure your materials are complete by the time reviewing starts, which at most programs is in January.
  17. Offering to refund your application fee is the very least they can do if the mistake was their fault. If they're not willing to do that, that's atrocious.
  18. As long as the letter is in by the time the application gets reviewed (likely January at the earliest), you should be fine. But, it's always best to check with each program.
  19. No need to be fancy, just tell them you won't be needing a letter from them because you have a sufficient number from other faculty. Chances are, they'll appreciate that you're taking something off their plate.
  20. I don't know of any programs that uses an auto-rejection rule based on a hard GRE cutoff. So, regardless of the range in which they occur (within reason; obviously improving from a 145 to a 147 isn't going to make you more competitive), incremental improvements in the GRE score are likely to have similarly incremental effects on your chances of admission.
  21. Don't sweat it. At worst, you'll make someone reviewing your app chuckle.
  22. Big difference between MS and PhD programs. That score is totally fine for all the former, but might be on the low end for the latter.
  23. Possibly, but such faculty are a dying breed. The trend in biostatistics is towards being more deeply embedded within the biomedical domains they specialize in.
  24. It doesn't hurt to put your GPAs, if they're good. Also, I wouldn't include any kind of summary/objective text on a CV. Regardless, there likely won't be anything on your CV that isn't on your application in some other form (except maybe publications).
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