<p>Yes. Fundamentally, biostatistics and statistics are the same; you can learn the same techniques and theoretical underpinnings. In fact, at many PhD in statistics programs, you can specialize in biostatistics or health-related statistics. The major difference is that since biostatistics is specifically focused on health-related projects, you will probably be required to take some classes you wouldn’t take otherwise.</p>
<p>Honestly, it doesn’t really matter which one you get if you know the techniques. A PhD in statistics who has, let’s say, an undergrad degree in biology and has taken classes in biostatistical methods (survival analysis, categorical analysis, time-series data) and does research on health-related topics can get a job at a hospital or health firm in much the same way that a PhD in biostatistics could. So if you wanted to get a PhD or an MS in regular statistics, you can. Many programs do offer a specialization in biostatistics. Even programs that don’t allow you to take classes in the department of biostatistics or other related departments (epidemiology, genomics, bioinformatics, environmental sciences, health policy) and create your own specialization. So in addition to biostatistics programs, I would also look at statistics programs at schools that also have strong offerings in the health sciences (like Columbia).</p>
<p>For example, let’s compare the PhD in biostats and regular stats at Columbia (that’s where I go).</p>
<p>Biostatistics
-Requires a master’s with introductory coursework in statistical inference, probability, regression analysis, experimental design, multivariate methods, and analysis of categorical data
-Required: intro to biostats, principles of epidemiology, probability, survival analysis, linear regression, design of medical experiments, categorical data analysis, GLM, multivariate analysis, a class on RCTs, longitudinal data, a consulting seminar, a doctoral-level seminar on statistical inference, and asymptotic statistics. They expect you to have taken some of that already.
-Electives include nonparametric statistics, RCTs II & RCTs III, genetic modeling, discrete analysis, higher-leve probability classes
-Requires a “cognate field” requirement like epidemiology, bioinformatics, computational biology, environmental sciences, health policy, etc. You must take a minimum of 2 courses in the same area
-Encouraged to take courses in other departments, including Statistics downtown and - through the Inter-University Doctoral Consortium - at CUNY Grad Center, Fordham, New School, NYU, Princeton, Rutgers, or Stony Brook</p>
<p>Statistics
-Doesn’t require an MA in stats prior to admission; you earn the MA on the way
-MA courses are applied statistics (3 courses), theoretical statistics (3 courses), probability theory (2 courses), stochastic processes, and stats computing
-You take 2 semesters of stats consulting
-There are no elective requirements other than that 1 course, and preferably 2, must be taken outside of the department. Other than that, you can take whatever electives you want in consultation with your advisor.
-Also in the IUDC, so you can take classes at all of the other NYC-area schools listed above as well as in the department of biostatistics. I am pretty sure that the statistics department will accept biostatisics classes as their own for electives.</p>
<p>So the basic levels are the same. Everyone is going to want you to take basic applied and theoretical stats, probability, and a statistical consulting seminar. Most places will also require GLM and linear regression modeling The major difference is that stats require stochastic processes, but we don’t use them that often in the health sciences so that class is not always required. On the other hand, we DO use a lot of categorical data analysis, survival analysis, longitudinal analysis and nonparametric statistics, so you may be encouraged or required to take those.</p>
<p>The other major difference is your consulting clients when you do your consulting seminar. This is partially influenced by the distance; the statistics department at Columbia is located in Morningside Heights on the main campus, whereas the biostatistics department is located in Washington Heights on the medical campus - 50 blocks away. So stats PhD students will mostly get non-health students for their consulting cases - business students, urban planning, architecture, education, psychology, sociology, that kind of thing. You may get some biology and environmental health students working on health-related projects, but you’ll get a range.</p>
<p>The biostats PhD students in their consulting seminar will get mostly health related projects - MDs from the med school, dental researchers, nursing researchers, sociomedical scientists and epidemiologists and environmental health scientists in public health, etc. But conversely, they won’t get the wide range that the stats PhD students are, because none of the business or education students are going to trek uptown if they can get the same advising on their own campus.</p>
<p>But in either department, you can do health-related research and pursue health topics for your dissertation and other projects. You may find more collaborations and support in a biostatistics department, though. In a stats department, maybe only 1 or 2 or a small subset of professors are working on health-related topics; in a biostats department, everyone is doing health related work and can advise you in your dissertation. But a savvy and motivated student can seek out advisors in biostats and even epi even if they are in the regular stats department.</p>
<p>Your job transition is going to hinge on your experience and prior job performance much more than your degree. Let’s say you’ve spent 10 years as a biostatistician for various health firms - the hospital, a university grant project, and maybe a health consulting firm. Now you want to move into doing statistical work for the operations research department at a local market research firm. If you know the techniques necessary for that kind of work, or have done similar techniques and can train yourself quickly - your transition will be smooth. Of course, the transition will be smoother the more work you do outside of university research.</p>