juilletmercredi

I was really confused by the 300 range until I realized that we were talking about the revised GRE. 300 range is scores of around 150 on both sections, which I think is good for the mid-level MPH programs (VCU, GMU, VTech) and probably also fine for UVa given your other accomplishments. Are you looking to stay in the DC area and/or attend a public institution in Virginia? Because if the latter is your goal - I applaud that, as MPHs can be expensive relative to the salaries you can expect. But if you want recommendations for other programs, I could provide that too, as public health is my field! (GWU does have an excellent public health program with the opportunity to intern in DC, but it's expensive.)

Well, I do teach about model assumptions - that's a classic part of the statistics curriculum and is very important! There's more than one way to do this; I have personally found it effective to start with classic model assumptions and statements, hinting at some ambiguity for my beginning students, and move to teaching more about variations and ambiguities as they begin to understand more of the theoretical underpinnings. And yes, of course, I have given thought to beginning with the ambiguities. So far, with my own students, I have found that it increases confusion. I think the difference here is also our subfields - you're quantitative so your concern is as much theoretical as it is application. I am in social psych, and when I am teaching undergrads, the concern is application. I LOVE to teach about the theoretical underpinnings and ambiguities in statistics, but given the demands of the departments I've assisted or taught in, that has not been feasible. But like I said, I don't leave out ambiguity altogether - I hint at it in my intro classes. For example, when it comes to level of measurement (like ordinal vs. continuous), I've included some trick questions to get students to realize that certain outcomes can be considered in different ways depending on the person. When asking students which test they would use, I've deliberately included questions that could be answered with multiple kinds of analyses, then we discuss. I just don't introduce it in the way I would with advanced or graduate students. Same thing in my consultations - the level of ambiguity I use depends on the interests and needs of the client. Some clients want to really know and understand the theory behind what's going on in their models. Some just need to get the models done for their papers, and in others the entire reason they hired me was because they don't really want to think about this too deeply. Given time constraints and resource constraints on projects it's often not feasible to explain and let people choose - and I have actually found that a lot of clients don't want to do this anyway. (Some do, and in those cases we have long exciting conversations about models.) Yes. Just as others are okay with the disadvantages/shortcomings of LPMs. I also never said that LPM was wrong or suboptimal. It's not about right or wrong at this level - just trade-offs in the strengths and weaknesses of approaches. I, personally, prefer logit or probit models because I understand them better. Convention of the field has a lot to do with it too, admittedly.

I had a feeling someone was going to bring that up. Yes, it's true that there are very few absolute "yes" or "no" answers in statistics/data analysis, but I have found that when I'm teaching statistics or doing statistical consulting with someone who doesn't have an intermediate/advanced grasp on statistics, telling them about ambiguity confuses sometimes. So I tend to use language that's more a standard "yes" or no, unless there's some compelling reason not to. I like to teach my basic stats students the "rules" so to speak and then teach flexibility of concepts to students who are taking more advanced classes (at least, that's the way I learned). OP sounded like he had more than two groups (although it was unclear). Personally I would not choose to use the LPM over the probit or logit models in the majority of cases, and I think that someone who wanted to would need to be able to clearly explain the strengths and weaknesses so they could avoid issues like the one Friedman had with that reviewer. But I think this is primarily going to be the analyst's preference and knowledge level, as the experience spunky posted seems to demonstrate

It depends on what you mean by a career in mental health. If you want to work with people who may have mental health disorders or problems - you might be able to get work at a clinic or center that helps folks and addresses mental health issues in a non-service-provision role. These positions generally are not well-paid, as was pointed out. With an MA in psychology you could also potentially get work as a research assistant/associate at a think tank, nonprofit, or NGO that does research on mental health. They do hire MA-level researchers, who work under the direction of a PhD-level scientist. But no, you cannot provide mental health services in the U.S. without a license. You will need to get a U.S. degree to get licensed, or perhaps investigate states that might allow you to get licensed with your int'l degree - but I doubt that there are many. Even U.S. clinical psychology MAs won't allow you to practice; the only master's level degrees that allow practice are school psych, social work, marriage and family therapy, and mental health counseling (sometimes goes by different names, but not clinical psych). Clinical psychologists exclusively have PhDs here in the states. I guess you could also count guidance counseling within schools, although sometimes that's more administrative. Psychology is the study of human behavior, and thus is widely useful and applicable in a variety of other fields. Psychology majors can go on to do law, medical, and business school - or they can do a variety of corporate, nonprofit, and public sector roles with their bachelor's degree. And like I said, there are SOME master's programs that allow you to practice with licensure - you just have to go to the right kind. Some people do an MA in psych as a stepping stone to the PhD.

Follow the money, IMO.

I didn't do my PhD in quantitative psychology but I do some research in that area, and I currently work in a methodology center with a bunch of quantitative psychologists. So I am also biased towards quantitative psychology - great subfield! But no, there aren't any MA programs in the field. There are some MA programs in measurement and statistics, usually in schools/departments of education, that will be similar. You could also get an MA in applied statistics at a place that allows some flexibility, and take electives in the psychology department. (A couple of the quant psychologists I currently work with got their PhD in psychology and a concurrent MA in applied statistics.)

Why do you want an MA in health psychology? As you mentioned, there aren't a lot of open direct opportunities for health psychology with a master's. Health psychology is my field. If you want to be a clinical health psychologist - and give talk therapy/counseling to people dealing with chronic or serious health issues, for example - you would need to get a PhD in clinical psychology with a health psychology focus or in a clinical health psychology program. If you want to go into academic research, you can't really do that with an MA in psychology in the U.S. You would need to get a PhD.

That’s very vague, and I would ask Professor Y what she meant about changes. I think if a professor is willing to say something like that, she should be willing to discuss in some limited depth what exactly the changes are and how she things they may affect a graduate student. (I have told people not to apply to my program before, but I have explained WHY I think they would be a poor fit.) No, it’s not audacious of you to ask a question about something that another professor explicitly brought up to you. If you don’t want to go back to her but you also don’t want to ask the POI, I would contact a current graduate student (look on the website or ask the departmental coordinator to put you in contact with one). They will tell you the details. My department also went through some “changes”, and I was pretty honest with prospective students who had heard about them and wanted to know about them. These changes had little to no impact on my education. So I wouldn't advise a student not to attend this department on that basis, but I do know a few students who gave more strongly worded warnings against prospective students coming here. But there were another set of changes that adversely affected student funding in the department in a particular track, so I would certainly advise a prospective student in that track to be careful applying there and evaluate their offer carefully. I wouldn’t say definitely don’t apply. After all, if you apply, that doesn’t mean you have to attend even if you get accepted. You might as well apply, see what happens, and if you get accepted you can visit and ask people in some more depth. The changes could be something really bad, or they could be something that won’t affect you very much at all, or they could be something that Professor Y is bitter about. But I WOULD say proceed with caution and assume that Y is a rational actor with good intentions and is waving a giant red flag for you. Also, your research interests sound SO SO INTERESTING.

Perhaps. I think you should go into this with the knowledge that your chances are lower because you don't have the prerequisites, and you are thus limiting yourself to fewer programs without a limited geographic range. That's okay, as long as you know that upfront. In the mean time, you should try to take some of the prerequisites inexpensively at a local public university so that you can apply to more programs in the future. But 6 hours' drive of DC is a pretty big range. That's pretty much everything from New Haven to Charlotte, and as far west as Columbus, OH. There are a LOT of universities in that range! University of Pittsburgh, UNC-Chapel Hill, Ohio State, UMD-College Park, Penn State, Temple, UNC-Greensboro, Gallaudet, GWU, Teachers College at Columbia, UT-Knoxville, Duquesne, Appalachian State, CUNY-Hunter, CUNY-Queens, Howard, Kent State, Loyola Maryland, St. John’s, West Virginia University, Case Western, CUNY-Brooklyn, East Carolina University, Hofstra, Ithaca College, Old Dominion, Towson, University of Akron, Adelphi, CUNY-Lehman College, East Tennessee State, Southern Connecticut State, SUNY Geneseo, Montclair State, Seton Hall, La Salle, Bloomsberg University of Pennsylvania, Cleveland State University, East Stroudsburg, Hampton, Kean University, LIU Brooklyn, North Carolina Central, SUNY-Fredonia…they all have SLP programs and they are all within a 6 hour drive of DC (+/- 15 minutes, but most are well within the drive. Penn State is only a 4-hour drive from D.C., for example, and they have a great program! Pittsburgh is also about 4 hours and that's a top 10 program.)

Taking graduate-level classes while enrolled as an undergrad is very common and quite different than being the equivalent of a full-time student in the department, but with no degree program enrollment. At my graduate institution 4000-level classes were actually mixed grad-undergrad classes, and typically ended up being primarily undergraduates anyway (mostly juniors and seniors). 6000-level and 9000-level courses were graduate only. But yeah, the reason a grad program wouldn't want you to do this is that you increase enrollment in the classes and take away time and effort that they would devote to their degree-pursuing students. There is also the perception that you would be less serious about the class than if you were in a purposeful degree or certificate program. There's also a certain premium placed on exclusivity and only offering their classes to students who are willing to commit to a degree program.

Good luck! I applied for MPH programs (and one PhD) in 2007-2008. I also applied and got accepted to to Emory, Yale, Columbia and Hopkins (and the PhD at Columbia, which I just finished in August). I should've also applied to UNC, and I'm not really sure why I didn't, especially since I didn't want to go to Hopkins at all lol. 1. Medium-importance, I would say. They won't get you in by themselves, but they can keep you out if they are too low. Your math score is quite low - that's in the 22nd percentile - so if I were you, I would study for the math section and retake. 2. Can't speak to chances, as it depends on a variety of factors. How long have you been working at that nonprofit? 2+ years of work experience can really help in this field, although I know tons of people who got in with less (including myself). 3. You need at least one recommendation from an academic contact, so if the only academic experience you have so far is from undergrad then yes, I would say you need one. You need someone who can speak to how you can perform academically in a graduate program. 4. I don't understand the question - they're not really much different from post-grad options anywhere else. They're totally dependent on the kind of MPH you get and the kind of experience you get. Like if you intern in the Capitol during your MPH you might have more options in the federal government than someone who doesn't do any kind of internship. MPHs can do a lot of things with the proper training and experience. 5. This isn't really a question, so again, not sure what the point is. If you work full-time at a public health-related nonprofit right now, it may be worth it to stay employed and attend the MPH part-time. I know at my SPH (Columbia) it was difficult to complete a full MPH part-time unless you have a very flexible schedule. The required core classes were usually in the evenings - but early evening, like epidemiology started at 5 pm so you'd have to leave work early anyway - but a lot of the electives are scheduled during the day, and most classes only had one section. (They did have a one-year accelerated MPH that was easier to complete part-time because there were fewer elective requirements). Full-time attendance is great if you can swing it, but also is more expensive because you have to find a way to support yourself while you attend full-time.

^What TakeruK said. If you are offered a funding package that is less than the amount of time it commonly takes to complete a particular program, then you should ask how often it is that people do get the funding that they need to continue and ask what funding sources they typically obtain. Also be aware that as an international student, you're not eligible for a lot of the most popular federally-funded external fellowships like NSFs, NRSAs, NDSEGs, Hertz, Ford, etc. Basically, it sounds like most students probably get on a grant with their advisor, so you would need to find a well-funded advisor in your first year who has a grant with a GRA that you could hop on. Relying on TAing part-time during a doctoral program is not ideal, because it's very time-consuming and doesn't really further your degree - so you want to get some TA experience but hopefully not have to rely solely on that for your funding.

$15/hour is more than reasonable, especially if you are in Washington, D.C. I actually think it’s a bit low - although I have lowered my tutoring rates for graduate students and personal connections. My husband charged $20-25/hour for freelance tutoring in Atlanta, and here in New York even low-priced tutors are easily $30-50/hour. So $15/hour is really good. I wouldn’t compare to the university/college rates, as in my experience institutions always pay less than you can get as a freelancer. I did statistical consulting for my university and I got paid $20/hour, but on the open freelance market I charged $30/hour to begin with and $50/hour later. Colleagues pay each other, when necessary. She's requesting an investment of time and, as OP pointed out, SHE was the one who brought up payment. It takes time to prepare for tutoring sessions and it also takes time to explain concepts to people, and time costs money. But besides that, colleagues develop fiscal relationships all the time in academia. For example, it's very common to put colleagues who know special skills on your grants as a consultant. There's a colleague I'm working on a project with as a consultant which comes with a pay rate. I've done statistical consulting for colleagues who I like very much - but I still get paid, because I am doing work. You can be a nice person and still charge for your time because it's valuable.

Don't worry so much about the names of degrees. What's really important are the courses you have to take and the skills you acquire in the program, as well as how the program looks to people who might hire you. An MPS, MA and MS might teach all the same things and be regarded equally by people in your field. The MPS, in particular, was begun by a few statistics programs who were concerned that regular MS and MA programs were too theoretical and not preparing students enough for professional practice of statistics in the corporate world. The goal is to equip students with the tools to go and become professional master's-level statisticians in businesses, nonprofits, etc. - as opposed to researchers who go on to develop statistical models in research settings and/or get a PhD. I think the MSP at Carnegie Mellon is similar in that regard. The MSE at JHU is simply a Master's of Science in Engineering. JHU offers two options - the MA in applied math and statistics, and the MSE in engineering, applied math, and statistics. The major difference appears to be the incorporation of engineering concepts in the latter option - to prepare engineers for analytical careers maybe in operations research and industrial engineering. The UW degree looks like a normal professional statistics degree. Basically, how you make your judgment is by looking at the required and elective courses. Most stats programs require pretty much the same thing - graduate-level intro stats and prob, a course or two in statistical inference, a course or two in linear regression modeling, and a capstone seminar in statistical consulting or some kind of final project. Some places require you to take an experimental design course; some places offer it as an elective. Some places require you to take an analysis of categorical data class; others offer it as an elective. If the program has these basic things as requirements and offer similar electives like survival analysis, multilevel modeling or longitudinal data analysis, time series data, stochastic modeling, nonparametric statistical analysis, maybe a survey data analysis course, structural equation modeling, multivariate data...etc...then it's probably a pretty normal statistics program regardless of the letters. Some programs add some concepts and classes from specific fields. Like you might find an analytics program that combines statistics and business together, and requires you to take classes in both. Some programs add some engineering flavor, and some biostatistics concentrations might want you to take epidemiology and/or natural sciences classes. Some programs require more computer science than others (many programs will require you to take a class or two, but some programs want you to learn a programming language). But if you want to be a professional statistician, take a look at the required course sequence and just make sure a program of interest has the above elements and/or is similar to other statistics programs that you know are solid.

I'm not sure that the department will allow you to do that. You'd probably have to contact each program directly (so in this case, Harvard) and ask if that is a possibility and how it works. You might be able to take a few classes part-time as a non-degree student, but I don't see any graduate program allowing you to be a full-time student in their department for a semester or year without pursuing a degree. I have seen a few cases in which students who are enrolled at another institution in a similar program have visited an institution for a little while, but it's normally to work with someone specific and do research, not take classes. When I was in grad school we had a couple of students at comparable PhD programs who were taking a semester or academic year to come work in the labs in my department for their dissertation research. But we never had anyone who was just taking classes with no end purpose/goal in mind. Can I ask why you want to do this?

Long distance relationships don’t always fall apart. I was in one for a few years with my husband before we got married, and we are currently long-distance again after a couple of years of happily living together. It’s not ideal - we want to live together, of course, but in academia such is life sometimes. I agree with Fuzzy - you can’t always put off developing your social life until you are “done”. Because your education/training/career has a way of never being “done”. Because after grad school might come a postdoc or adjuncting or a VAP in another city; and then may come a tenure-track job in a fourth city, and you might decide to move to a better job or have to move because you don’t get tenure. Non-academics do this, too. They move because of job opportunities, or move because they hate the weather, or whatever. THIS is your life, right now, and you have to live it. If you are going to a doctoral program, you will be there for five to six years at least - that’s a long time to completely avoid entanglements. And you never know what might happen. You might date some people, but it simply doesn’t last that long. Your partner might agree to move with you wherever you go next (my husband would’ve moved with me to my remote college town in the middle of nowhere if he wasn’t still in school back in Grad School City. In fact, he’s planning to move here as soon as he’s done, next December). You may fall in love with your grad school city and find a way to stay. I know people in all three of those kinds of situations, too - people who stayed where they met a partner, people who moved to where their partner was and made their career work, and people whose partners followed them. With me and my husband, we stayed in communication about it. When my husband was in the military, I was willing to move with him if he decided to make a career out of it and just make it work. When he separated from the military and decided that he didn’t want a career there, he made it clear to me that he was willing to move with me to where I find a job, within reason. In return, I’m committed to finding a place where we can both have fulfilling careers and enjoy it, which means I’m more flexible about not necessarily working within academia (although I never was really attached to the idea anyway). I’m not in school anymore - I’m a postdoc. But you kind of just have to trust yourself and your partner and trust the process.

No, you can't do that. Or rather, it's technically possible to do it in SPSS (aka, the computer program will run), but it is theoretically/conceptually going to give you junk. OLS linear regression relies on the assumption that your independent variable has a linear association with your dependent variable; the outcome needs to be continuous, because there's no linear way to map out nominal values if they have no order. Your results will be meaningless, if you even get any. (You could do an OLS regression on ordered classes - that's not good, either, and there's an ordinal type of regression that's much better.) If your outcomes are nominal (unordered) and you have three or more, you really need to do a multinomial logistic regression (or some kind of other multinomial generalized linear model - but multinomial logit is likely to be the best). In a multinomial logistic regression, you set one of the categories as the base/reference group and compare the other 2+ groups to the base group. The interpretation is relatively simple if you don't have a bunch of covariates or interaction terms; IDRE at UCLA maintains a help page on it here. If you only have two groups, you do a logistic regression instead. They are both conceptually similar to OLS regression - the interpretation is different, though, because the shape of the curve is quite different (you talk in terms of (log) odds or relative risk instead of simple linear increases).

Yes, I think generally speaking if a department allowed you to take classes as a non-degree student that research experience would not be important - however, many departments would not allow you to take classes as a non-degree student unless you were in some kind of non-degree program (like a certificate program). Many would, though. It would just vary from place to place. In my selective PhD program I don't think we ever actually had any non-degree students in the grad-level classes. Our post-bacc students were primarily there because they wanted to get a PhD in the field but lacked the undergrad preparation in the field, so they were usually taking undergrad-level classes. There were some mixed grad-undergrad classes that had undergrads, post-baccs, and grad students - but the regular graduate-only classes wouldn't have taken a post-bacc student.

I had a 13" MBP during the later years of my doctoral degree but I also purchased a 24" monitor and hooked it to an external keyboard and mouse. Best of both worlds, IMO. I don't really think you need a 15", unless you absolutely hate being tethered to a desk ever. Sure it looks nicer to watch movies and do data analysis on it, but IMO 15" is still too small for data analysis. I love my 24" screen for data analysis and writing at the same time, or looking at results while writing. When I'm at home if I am on the computer during work, I'm at my desk. I only take the computer away from the desk if I am doing something for fun on my couch or in bed. (In grad school, I occasionally used my MBP to write away from my desk at home - like in a coffee shop. But I only did that if I knew I was only writing or reading articles that day. I rarely attempted to do data analysis on that tiny screen.) My new work setup is a dual monitor set up - a 21.5" iMac with a 22" Dell monitor to extend the desktop and OH MY GOD. This is what bliss is like. (I'm a methodologist who spends a good bit of my time doing some kind of data work so...it gives me the feels.)

You don't have to contact them ahead of time, but it can't hurt to mention them. When I applied to MPH programs, I did so with an eye to getting into PhD programs later and I knew I wanted to do research. So in each of my statements I mentioned 2-3 professors whose work interested me, but I didn't contact any of the professors ahead of time. I did reach out to a professor at a program I got accepted to after I got accepted, because I was soooooo excited at the prospect of working with her, and she seemed interested in me too. The admissions process works so differently for MPH programs - admissions is usually handled by administrators and not professors, so your expressed interest directly to professors won't necessarily make a difference unless they fall in love with you. But mentioning faculty interests among other things in your statement shows that you've done your homework and that you have concrete reasons why this program is a good fit for you, which impresses the admissions office.

Do you mean research fellowships for graduate students? I'm assuming you do since you name SSRC and NSF. It really depends on the individual fellowships, their rules, and where they come from. One big rule is that you cannot hold two federally-funded fellowships at the same time. So, for example, you can't receive funds from NDSEG and NSF at the same time - although you can be a fellow from both at the same time. NSF GRFP, for example, allows you to place the funds on reserve for up to two years. You have 5 years to use the entire 3 years of money. NDSEG does not allow ANY deferrals, and is also 3 years. So what if you get an NSF and an NDSEG at the same time? Usually you'd put NSF on reserve for 2 years while taking the NDSEG. Then you would decide which one to forfeit one year of. In the old days, you would forfeit a year of NSF and take the third year of the NDSEG because it was more money, but now the NSF is slightly more money (just slightly - an extra $500 a year). But the NDSEG also covers your health insurance and all mandatory fees; the NSF requires your institution to do so. So it would really be a decision on your part (and your department's). After that third year, you'd spend the next two years on NSF. Dissertation grants are the same. You can't use two federal sources at the same time for your stipend, IIRC, but you could potentially use SSRC and NSF DDRIG (or whatever they are called now) at the same time. The SSRC grant is for proposal development anyway, and would generally be taken sometime in years 3-4 while you are working on your proposal; the NSF one would be more sometime in years 4-6 when you're actually working on the dissertation itself. But let's say you got an NIH R36 and then an NSF DDRIG, I don't think you can take both nor can you defer them, so you'd need to decline one. Basically...it really depends on the individual grants.

I am in the social sciences. I applied twice and thought I didn't have a chance in hell, especially after I got not even HM my first year (2009). I got it in 2010. I also have a friend who is a health historian who just received one this year. So do it anyway! The time is so worth it, and you can repurpose your statements at least in part for other things, too. You are kind of doing both. Your reviewers are going to be people within your field - which is why it's really important to make sure you apply to the correct section, because your reviewers are going to be comparing the strength of your application to the strength of other applications that they are reviewing. So directly, you are only competing with other anthropologists. BUT at the same time I don't think the number of awards is pre-allotted per field (or at least, it wasn't before), so in a sense you are kind of competing with everyone else - your application needs to show promise as a strong overall scientist, not just a strong social psychologist or whatever. For graduate school applications, there was usually a field where you could discuss any anomalies. I mentioned this briefly, but always talked about what I learned from the experience and how it has made me far more resilient. I took 2 years after undergrad to do some coursework and published 2 first author papers to prove myself a bit before grad school. (Papers weren't even published for grad school apps, they were published recently). Should this be mentioned anywhere in the application? I wouldn't. Aside from this being very difficult to pull off, you also don't have a lot of space - and you want to spend the space you do have focusing on the qualities that make you qualified for the GRFP. While resilience is an important quality in a scientist, they don't really want to hear about that - they want to hear about your research experiences and interests. If you have a recommender who could speak to it, they can do it more delicately. That's what happened in my case; one of my recommenders handled that (wishy-washy junior year grades) and I acted like it never happened in my statements, lol. On the subject of perfect applications - YES, do attempt to make your application as perfect and error-free and pristine as possible. BUT, if you are reviewing it after you turn it in and find a typo...don't panic. I had one minor typo EACH in my personal statement and research statement and I still got the award. (And about ten million people read my statements. Everyone missed it!)

Yes, I think you are paranoid. While your boss may get irritated that you leave a new position a year in to go to grad school, few sane bosses will take it as far as calling your graduate program to rant about yout. And even if they did, most programs would realize that reflects more on the boss than on you. I don't think it's immoral or inappropriate for employers to ask about it, though. "Are you married?" or "Do you want to have children soon?" are completely different questions than "Are you planning to leave for graduate school soon?" The former two first of all give the employer the potential to discriminate illegally against candidates, but second of all have pretty much zero bearing on the work of the employee. Many, many people work hard while being married and/or having children. These questions and the discrimination that comes along with them is more about age-old stereotypes that won't die than any actual impact on productivity. However, future graduate students aren't a protected class. Moreover, most students do plan to attend their grad programs full-time, which would probably mean quitting the job, so it does have a very real impact on the job. There are some jobs in which high turnover would be kind of disastrous. It's also not uncommon for interviewers to ask these kinds of questions - maybe not about grad school, but about where you see yourself in 2-5 years and/or how long you think you would stay in the position. (And I think contracts for length of time are unenforceable on the employer side.) I'm not saying that I don't think employers should ask about grad school; but I think it's understandable if they are a bit irritated if you leave after 9-12 months when they wanted someone to stay for 2-3 years. Now, that's not really your problem, of course. People get irritated all the time and they have to get over it. Employers who screen out anyone who thinks about going to graduate school also run the risk of screening out really competitive people (and who knows, they may change their mind and decide not to go at all, or may not get admitted anywhere).

Someone might have told you that you shouldn't pay for an MA in English - but did they mean that you shouldn't pay because there are abundant funded English MA programs, or did they mean that you shouldn't get an MA in English at all? Because English is not my field, but as I understand it there aren't really a lot of English MA programs that are funded as a matter of course. Some English MA students may fund themselves through teaching assistantships. Now, many programs offer funded PhD programs in which you can earn a non-terminal MA on the way - usually by writing some kind of master's essay/thesis. They don't admit students who only want to do the MA, but they do have the mechanisms in place to confer the MA to enrolled PhD students who complete the requirements.

Congratulations! I really hope you enjoy Oxford! And just because this was kind of bugging me...I just wanted to add more generally (for anyone searching this later) that the prestige of a university and/or the offer of funding should NOT be the major thing that makes the decision FOR you. By which I mean, "because it's Oxford!" is not a good reason to go or stay to/at a PhD program if you are unhappy and/or not sure if that's a step you want to make. It turned out being the best thing for the OP, which is amazing! But this could also apply to any U.S. university too - "because it's Harvard/Stanford/Michigan/Berkeley/wherever!" I had this struggle too, when trying to decide whether or not to quit. It's totally amazing to get admitted to a prestigious university with funding to afford it, but it's still a 5-7+ year program that will require a lot of sweat and tears from you, and it might be completely unnecessary given your life goals. So I urge anyone else who stumbles across this and are reading the responses to try, as much as possible, to remove the prestige of your university and of any funding sources from the equation and think about this personally and professionally - do you need to do this PhD to get the jobs that you want? And will you enjoy the means as much or almost as much as the ends? In other words, are you okay with the idea of toiling for 5-7 years for the degree and then not getting a tenure-track professor job or a prestigious national lab job?