mittensmitten895

Based on my conversations with other admitted students, it seems like this board skews heavily towards the "traditional" PhD applicants. I know it would take all of about 10 seconds for certain people to figure out who I am based on this information, but I'm nevertheless putting my profile out there in the name of sample representativeness. Undergrad Institution: Big state school (ranked 70's) Major(s): Microbiology, with medical/public health focus Minor(s): GPA: 3.67 Type of Student: DWF Grad Institution: University of Michigan Concentration: Biostatistics MS, Epidemiology MPH GPA: 4.0 (A+ = 4.3, but max cumulative GPA allowed is 4.0) GRE General Test: Q: 800 (94th) V: 770 (99th) W: 4.5 (67th) GRE Subject Test in Mathematics: N/A Math/stat preparation: 4.0 in Honors Calc II, 3.0 in Honors Calc III, 4.0 in linear algebra, A-'s in early biostat grad classes that got cancelled out by A+'s later on, advanced calc/real analysis in progress now Programs Applying: Biostatistics PhD, Epidemiologic methods ScD Research Experience: Lots of epidemiology research experience starting in undergrad. Involved in design, conduct, and analysis of a few small-scale studies. Funded for two years of grad school as the data manager and stats consultant on a medium-sized cohort study with some fun statistical challenges. Awards/Honors/Recognitions: Full-ride merit scholarship for undergraduate, Honors College in undergrad, Dean's Award merit scholarship for grad tuition, a conference travel award, selected to be a student speaker at our school's causal inference symposium Pertinent Activities or Jobs: Besides being funded through a research assistantship during grad school, I interned as a data analyst for two summers at a local research non-profit; some public health volunteering pre-grad school; post-baccalaureate research fellowship in epidemiology pre-grad school Letters of Recommendation: (1) Linear regression/GLM sequence full biostat prof who I also worked with on several projects during my internships, (2) internship supervisor (no PhD, but MS biostat) who directly oversaw the manuscripts I prepared during my internship, (3) assistant biostat prof from a survival class I aced, (4) full biostat prof from my clinical trials and consulting capstone course -- I would guess that (1), (2), and (4) were outstanding recs and (3) was good to great Any Miscellaneous Points that Might Help: Longstanding interest in causal inference that made it easy to connect a somewhat nontraditional background to my proposed area of research. Only applied to places where I had a potential dissertation mentor/topic combination in mind. Spent a lot of time on my SOPs so that it was clear how and why I ended up in biostatistics. Some academic service (ad hoc and search committees, etc). 1 pub + 2 more in progress + a few conference abstracts. Applying: Michigan Biostatistics PhD - Accepted 1/24, current funding would continue as long as I make academic progress UNC Biostatistics PhD - Accepted into DrPH program 2/3, never heard about funding Berkeley Biostatistics PhD - Rejected 3/18 Harvard Epidemiologic Methods ScD - Rejected 3/7 (I was told pre-rejection that they thought I would choose the funded biostat offer... yep) Harvard Biostatistics PhD - Accepted 2/10, standard 4-year funding package

I am just finishing up my general epid MPH at UMSPH. I am a dual degree student, so my experience might not be typical; nevertheless, I thoroughly enjoyed all of my epid classes and felt like I got a great education for an unbeatable price. I originally debated between Columbia and UM, and I am so glad I chose UM because now I am not burdened by huge amounts of debt from NYC's high cost of living. Generally, people seem to respect the UMSPH brand and I don't feel at all like I'm missing out on opportunities because it's not an Ivy. I stayed academic with my extracurriculars by becoming a member of a bunch of academic service committees, but I am always surprised at the diversity of what students are doing. There is a way to get involved in whatever aspect of public health you care about (nutrition, air quality regulations, patient empowerment, etc). Although I am not personally going into public health practice, I believe Michigan's connection to that world helps keep it grounded and focused on what we can do right now to improve population health. As for weather -- this winter was crazy cold, but it's usually not that bad. Ann Arbor is designed to accommodate cold weather. I am considering Harvard for my PhD and I was surprised by the number of students saying they had 25-minute walks to HSPH with no alternative method of commuting. I like my 25-minute walk to UMSPH right now but I also like that when it gets cold (or, realistically, when I get lazy) I can hop on a free bus and spend less than 5-10 minutes outside. Some people seem to mind the cold more than others, but it's not unbearable. Hope this helps!

Yeah, I think you have an unidentified weak spot in your application if you applied broadly and got few offers. You don't say where else you applied, but I think you could have expected more favorable responses based on what you've said here. Another year of experience might not fix whatever red flag might be killing your app. (Also, is that quant GRE for real or was it switched with verbal? A 155 after your math training would be worrisome to me.) As for reputation? My guess is that people feel like you are turning down a good option that may not be available to others now because you applied (and got into) somewhere that you apparently didn't research even a little bit beforehand. Also, a quick google search would have revealed that BU and Michigan are not in the same league, so that didn't really help your case for preparedness. I personally didn't ding you, but in the end they are worthless internet points and you shouldn't give them another thought.

I was actually going to say something about SMART but wasn't sure whether that's actually a big deal or just something that seems like a big deal to me because I'm at Michigan and working on a related topic. Susan Murphy does not have a joint appointment in biostat, but she definitely serves on dissertation committees for the biostatistics department. Tom Braun does some cool stuff for Bayesian Phase I dose-finding and also happens to be one of my favorite professors ever. Some other big faculty work on analysis of trials, but it tends to be in the context of a specialty like missing data, cancer, time-to-event, etc. For example, I just got an email this week about a defense in Jeremy Taylor's group on adaptive trial design for cancer treatments. (Also, someone in my office block graduated last semester and took a job at MD Anderson after completing a dissertation on some survival topic not directly related to trials, so there's that.) It seems like there are better fits out there for you, but if you'd rather not wait another year to start your PhD then you should know that choosing Michigan would not condemn you to a career in statistical genetics research. The two-body problem cannot be helped, though =(.

I'm sure you took this into consideration in other ways, but the data you're presenting here do not answer what I would consider to be the more important question for someone wondering if he or she has a shot at a TT position after attending University X. That question is: "among new University X PhD graduates actively pursuing the tenure track option, what is the probability of landing a job at a tier 1, 2, ... , n department?" Your argument is missing the denominator necessary for that type of calculation. I freely admit it's a difficult denominator to get, but its absence cripples attempts to accurately assess TT prospects. Moreover, there are a whole slew of steps in between accepting a PhD offer and starting a TT job search, and you should know where people entering University X with TT intentions typically drop out along the way (including why, what happens to them instead, and how they feel about it). You can't get that information by looking only at the (relative) successes, i.e., grads who end up in faculty-like positions in departments worthy of your consideration. I'm not trying to say you personally haven't thought it through. I'm sure you have. I'm just trying to point out the difficulty in drawing meaningful conclusions from the available information.

Math is a special case. Most undergrads need high-quality math instruction, and many will need multiple classes. That's a lot of teaching demand. Plus, the quality of students/faculty and lower-ranked math programs is still pretty good. Have you seen some of the stats for rejected math PhDs? It's crazy competitive and I'm glad I'm not judged against that applicant pool. In biostats, a successful department is one with access to plenty of collaborators with grants -- there's a reason the current US research infrastructure can't support 100 good biostatistics departments. I assume pure statistics is somewhere in between, but I don't know and you should make it a point to find out if you're interested in the TT route. I guess what I'm saying is not to let your experience in math give you a distorted impression of the TT prospects for another field. Things can be very, very different in different disciplines. Many people later disappointed by the lack of TT job spent their grad careers enjoying the signs and hints that it was possible (yay! people love me and my research!) while ignoring all of the opportunities to find out whether it was actually true (maybe people love it but the love does not extend beyond a contract position without health benefits...). After all, the question is not whether someone from University X can get a TT job but what percentage of their TT seekers ended up in suitable positions/how exceptional the University X candidate had to be in order to get the interview.

Just got my rejection from Harvard Epi (Epi methods ScD track). I knew it was coming since my POI (joint biostat/epi faculty) emailed me last week to let me know that they felt fit was better with biostatistics and that I would likely choose that (funded) offer over one from epi. I said as much during my biostat interview so it's not they were making huge assumptions about my preference. It is kind of a relief to tie up a loose end, though. Congrats to those who got in!

Yeah, this definitely figured into my choice of where to apply. I'm too happy with my career options right now to feel like it's worth pursuing a PhD only to fail quals. I heard that Hopkins biostat used its qualifying exam as a weeding mechanism and promptly lost interest (also... Baltimore). Berkeley biostatistics also has the same reputation but not quite to the same extent. Michigan had insanely difficult quals last year and has the same exam chair this year, but they are usually not intended to weed people out.

I kind of agree that when I see a comment that comes across as exceptionally entitled, I can guess it has an "I" next to it. You also have to keep in mind that the competition for international slots at the top schools is so ridiculously tough that if they believe they have a shot then they probably have not encountered much failure in life. Plenty of international applicants have done everything right and yet find themselves locked out when objectively less qualified domestic applicants get in. That can't feel good. The other reason might be that readers are more sensitive to connotations and word choice when something might be construed as boasting. Here, the language barrier might be leading native speakers to misinterpret the tone and intent. For example, I knew ahead of time from discussions with adcom members that I was probably going to get into Michigan's program, but I would never say I "expected" to get in because I know that it sounds annoying and arrogant when I simply want to convey that at some point I had prior knowledge that it was likely to occur. Even now I feel uncomfortable having typed out those words because I understand the connotation. Since 99% of the international students I know are exceptionally humble and gracious, I am inclined to think the occasional grating entitlement in the results survey is just a combination of poor word choice and frustration at a particularly dark moment.

I think Harvard epidemiologic methods ScD results should be out fairly soon. A POI emailed me yesterday to let me know that since I got into the biostatistics PhD and seemed more likely to accept that offer than one from epi, I probably won't receive an offer from epidemiology but that I am welcome to work with any of the jointly appointed professors. Oh, well. They weren't wrong. Honestly, I feel like it was worth paying the two application fees to make sure I ended up in the right department. I wasn't sure how applying to two departments would pan out, but I have to say I'm impressed with the care and thought they seem to have put into evaluating fit. My only regret is that some of my application fee ended up going to support that godawful SOPHAS.

I did the biostat MS at Michigan and we had several shared classes with the applied stat master's students. This is just my opinion, but it felt like the MS biostat provided more rigorous training than their program due to their program being lighter on credits (30 credits vs. 48 credits). It's certainly not a gateway to theoretical statistics PhD programs, but that's why they call it applied statistics. The consulting course was supposedly very helpful for international students and students without much experience interacting with non-statisticians. I personally do not feel like the program ends up giving enough extra knowledge/experience to justify three to four semesters of time and tuition, but it depends on your situation/background and what you want to do with the degree. I wanted and needed a lot more training to get myself up to the level of an MS/MA statistician than that program would have given me. That said, my friends from that program have had pretty good job placement. It did take them longer than they wanted to find their positions, though (~ 6-8 months).

I also came from a non-math/stat background, although I had more a quantitative orientation than it sounds like you have. I found that it was important for myself and for others that I was able to articulate how I arrived at my interest in biostatistics. For people changing fields, it helps to have CV items that tell the story of your trajectory so you aren't continually explaining yourself. It shows you know what you are getting into and didn't just decide on biostatistics because you flipped open a career book and felt like it was a career you could see yourself doing (yes, this really happens, and it often goes poorly). You can tell that story with other research or volunteer experiences, but a one year program in epi/biostat could be a good, low-cost way for you to see for your own benefit if you really like biostatistics or if you would prefer to stay in applied research. If you end up liking biostat and want to pursue the PhD, it also demonstrates to others that your newfound interest isn't just a passing phase. Because of a somewhat winding path, I will have an MPH epi and MS biostat from 3 years (90+ credits) of grad school. It was a long slog, but I definitely use training from both fields on a daily basis. Just make sure you lean towards the statistics classes as much as possible -- in my experience, the "bonus" insight from epi really only kicks in once you've mastered the stat basics. I know it's not exactly the curriculum you're contemplating, but I've found my dual background to be highly valued on the job market. It don't feel that it has kept me from any academic opportunities I wanted, either. This is all just the perspective of a student situated right between the two fields. Some of the biostatistics faculty members on here can probably tell you more about how this would be viewed from the PhD admissions perspective. Just remember that getting into a PhD program is only a good thing if you actually want to be in that field. Good luck with your decision!

What a ridiculous statement to make! You have a small window into the admissions process and suddenly you can make a better decision than a whole committee of experienced Harvard faculty members did with a lot more information than what you see here?! It sounds like sour grapes on your part, and you should wonder if your entitled personality is holding you back from attaining the success you "deserve." P.S. You're screwing up our already-skewed sample by discouraging certain types of profiles from reporting. I hope you're not interested in survey research.

... kind of? It's not as in depth as you would find in math or stat departments, but it is touched upon. Michigan biostatistics does Casella and Berger for its first year MS theory courses, and students planning on a PhD currently take a 2-course sequence in the statistics department that covers some measure theory. (I say "currently" because I've heard they are revisiting this requirement.) The material from the higher level courses shows up on the qualifying exams. Because I was not planning on a PhD in biostatistics until just a few months ago, I have not taken those classes. So I know measure theory matters at least a little in biostatistics because it's delaying my quals by a year =). I would guess you might also find measure theory in required courses at UNC biostatistics because of its theoretical orientation.

Even if hiring committees don't care about coursework, your curriculum can affect academic job opportunities by shaping your selection of research area, your approach to a chosen research problem, your ability to understand and incorporate relevant literature, etc. I haven't taken measure theory yet, but people who think it is important seem to believe it is very important. (BTW, cyprusprior, this is a great question. I'm eager to hear what others have to say on the issue.)