spunky

well, the fact of the matter is that very few people come into Quant Psych/Psychometrics graduate programs with a lot of mathematical or programming skills. most people in these programs are undergrads in psychology that also have a knack or an interest for data analysis and over the course of their MAs/PhDs and they become good at it. does it help to have a background in math/stats and some programming ability? oh, absolutely! i did my BSc in Mathematics (with a heavy concentration in Statistics) and that allowed me to jump right into research from the very beginning. i didn't need to take the research methods courses/statistics to be aware of the issues because i had already studied them. HOWEVER, once the other people in my program (actually i should say 'person' because only one other guy applied to my program when i started) were done with their courses, they (he) was sufficiently proficient to conduct quality research and ask interesting questions. everything you need to know to become a good researcher will either be taught to you or you'll learn it as you go by talking to your more advanced/geeky peers, self-studying or by googling (Google will become your new best friend, trust me on that). but you also need to keep in mind that Quantitative Psychology (like other areas such as Mathematics or Statistics or Physics, etc.) will demand hours of alone time between you and a computer programming things over and over again until you can get them right. the main tool of the modern quant is the Monte Carlo simulation method (or 'simulations' for short). maybe you'd want to look into what they are because, in this field, you will be programming A LOT of those. this (and other stuff) is the one thing i do warn people about because this sub-area has a lot more to do with STEM fields than Psychology. but you could potentially go for a more 'applied' path in which you take on projects from other areas (clinical, social/personality, cognitive, etc.) that require complex modeling and maybe becoming an expert on this kind of analysis. for instance, a lot of Quants are being scooped up by people who do brain imaging research in biopsych/neuropsych/psychiatry/neurosciences/etc. because fMRI data is notoriously difficult to analyze, and methodology experts who can adapt methods to this type of data are badly needed as well. whether you feel you can 'contribute' to the area of not really depends on your research interests. i'm very theoretical and i really like to do math and programming for its own sake (which also impresses people when it comes to looking good on your CV). but you could also focus on learning how to apply complex methods to other areas of psychology and that can be your contribution. it's really up to which adivsor and which program you choose to enroll in because there area some people who are more 'theoretical' (like the UCLA or Urbana-Champaign crowd) and some are more applied (like the Educational Measurement people at Standford). i think if you work hard you'll be able to become a good researcher in Quantitative Psychology but the question i'd like to pose to you is more along the lines of what Applemiu said of how in love are you with stats? because, trust me on this one, you better be ready to get married to this stuff or a few years down the line you'll start hating it. Stats is like music or a foreign language: you only get good at it if you practice, practice, practice!

well, as a quant i have to say i'm biased towards the awesomeness of my field ( 'cuz we're sorta awesome ) and like to point people towards this (horribly outdated but still) chart from the APA website: http://www.apa.org/research/tools/quantitative/?item=6 when you say you find the field "intimidating"... what do you find intimidating about it? it's important to keep in mind that this field goes a little bit beyond just data analysis. you'll be pushed to sort of think like a statistician and deal with some non-trivial math stuff or handle complex analyses. you'll also have to be good at computer programming in statistical software (more specifically R. ok, STATA and SAS can come along as well). but SPSS will no longer be enough for the type of research us quants do. what makes you consider Quant Psych as a potential field of study? are you interested in measurement issues (i.e. psychometrics)? or more data analysis?

Uhm… I guess that sort of reflects a little bit the difference in backgrounds where we come from (I come from a Math background and switched to a social science PhD). It is true that in most social science programs the “rules” are taught first and the rationale comes later. The drawbacks I’ve found, (coming from a very different program and very different way in which this stuff is taught) is that students can either (a) become extremely fond of ‘cookbook’ approaches to data analysis (robbing them of flexibility that we’re supposed to foster) or ( b ) have to re-learn a lot of the crucial stuff they learned before because, suddenly, everything they thought was set in stone does not necessarily hold all the time. But say… what if you were to teach (or explain) from the very beginning the inherent assumptions that each model makes? Granted, this takes a lot more effort to teach than the “hard rules” approach (and I know that from experience because that’s how I teach this stuff, from the intro courses to the advanced stuff, like my math professors did) but it helps create a deeper level of understanding from the very beginning. You force people to acknowledge the ambiguity and complications that come with every day data analysis and help them find ways to deal with these ambiguities. The key issue is, of course, that the emphasis is now on the theory behind the method and not necessarily the application of the method (which most methodology courses concern themselves with). But your students or the people you consult for will grasp things a lot better right from the start. I also got the impression that the OP had more than two groups (although there is a multinomial linear probability model) but, still, I think when you mention Friedman’s reviewer you help bring to light what I elaborated on before, particularly when he says: “I believe our referee was stuck on a non-linear binary response model simply because that is the “correct” approach that we are taught in graduate econometrics”. In Friedman’s view, the reviewer had issues with his approach because of tradition. You’re taught to do certain things in certain ways as a graduate student and that’s the way you have to do it. Then when you tell your students that only certain things work in certain ways and that’s how they have to do it. A lot of malpractice can get perpetuated this way, some of which can have horrible consequences. The popularity of robust methods during the 80s-90s which led to a delay on the discovery of the ozone’s layer hole comes to mind. In our particular case, you say you’d not use the LPM over the probit/logit model in the majority of cases. Does that mean you’re also OK with leaving endogeneity in your probit/logit models in the majority of cases? Because I’m willing to argue endogeneity gives you *more* problems than LPM models have, it’s not easy to fix for probit/logit models and it’s EXTREMELY pervasive. So maybe you have (inadvertently, of course) helped perpetuate a more severe form of malpractice because you consider the LPM model to be wrong or suboptimal. Now I’m not blaming you of that (most of the time we don’t even acknowledge the problem of endogeneity within psychology/education/sociology, etc.) but it helps me make the case that, regardless of the research question or the level of the person you’re dealing with, it’s always important to leave the door open to all pertinent options. Just get down (or up) to their level of understanding, explain what each method does and let them make an informed decision of what seems to work best for their data. I bet you’ll surprise yourself about the new stuff you’ll learn every time!

we are moving to a point within the social sciences (or science, in general) where there simply is more data to be analyzed than people capable of doing it correctly. about 10 yrs ago the APA came up with its taskforce to increase the number of PhD students in Quant Psych because they were panicking at the possibility of good methodologists and properly-trained data analysts becoming extinct within psychology. http://www.apa.org/research/tools/quantitative/quant-task-force-report.pdf michael edwards from Ohio State did a follow-up like 5 yrs after the taskforce efforts began and another one i think in the 2012 Int'l Psychometric Society annual meeting with the results being somewhat the same as when it all started in 2005: the output of Quant Psych PhDs has remained the same but the need has grown. a combination of professors retiring and the allure of the private sector (which is starved for computer-savvy data analysts and offers salaries that are a little too-good to resist) makes it difficult for the field to grow. i always try to encourage people to consider Quant Psych/Psychometrics as a potential area of study (even if it's not your primary interest) not only for the flexibility it offers but also because it helps keep the field alive. we don't wanna go the way of Mathematical Psychology, may it R.I.P.

for the sake of completeness to this forum thread i think it's important to point out that it IS possible to run OLS regression with a binary dependent variable (0/1) and getting something that is NOT "junk" or "meaningless". it's called the linear probability model, mostly developed within econometrics. even though it's been around for +50 years, econometricians still debate its relative merits VS the use of probit or logit regression (latest overview of the debate here: http://blogs.worldbank.org/impactevaluations/whether-to-probit-or-to-probe-it-in-defense-of-the-linear-probability-model after many years crunching numbers i've learnt to realize that there are very few absolute "yes" or "no" guidelines when it comes to good practice within data analysis. the answer to pretty much everything is a big fat "it depends"

have you looked at APA's Division 5 website where all of us, quants, hang around? or a nice overview of quant programs in the U.S./Canada can be found in: http://www.apa.org/research/tools/quantitative/?item=2 from a completely biased and absolutely subjective opinion i think quant psych/psychometrics programs are awesome and you'll thank yourself later on once you figure out this is the area with the best employment prospects both inside and outside academia within psychology. trust me, i'm a quant!

honestly, this sounds like financial suicide. i don't think the job market is that great for you to be able to pay all that unless you get help from spouse/parent or are prepared to live a VERY, VERY frugal lifestyle for a VERY, VERY longtime.

sorry, it wasn't until i re-read your thread that i realized my initial suggestion wasn't gonna work (but i couldn't edit it). theoretically you could get a research position only with a Master's, but the competition is tough (among people who will more likely than not have PhDs, so that places you at a disadvantage) so.... uhmmm... ok, the way i see it you have two choices: (a) go back to school and enroll in a more lenient program (like Counseling Psychology or Social Work) and just soldier on, get your degree (and those coveted supervised-hour internships) and work on that OR ( b ) just put the "career in mental health" thing in the back burner to get a job that pays the bills and then go back to option (a) when you feel you're ready for it. this may not be your case but here're my 2 cents. i've done some volunteer work with NGOs targeted to helping educated immigrants navigate the process of getting their credentials validated (in Canada) to see whether they can land a profession similar to what they had in their original country. i'd say that close to 90% newcomers don't get a position like what they had before (which can be very frustrating but that's life), so the focus is on getting them employed doing something...anything that pays the bills and then start thinking about career planning. if your end goal is to work in mental health you will have to get some sort of licence or certification somehow but if you can't get it right now (or go back to school to get it) then you just need to open up to a few other possibilities. you may be surprised at what other talents you have hidden that have nothing to do with your area of study

getting licensed is a VERY big deal in North America (Canada/U.S.). so aside from very menial and not-very-well-paid positions, there isn't much you can do without a licence. you'd probably be aiming to become more of a 'care-taker' of sorts. you *could* potentially aim to become something like a 'life coach' which is the term i know people now use to do something that looks like therapy but aren't really licensed. there are various issues with this, though.. as you can imagine. not being regulated means someone like myself (who has never had supervised training) can claim to be a 'life coach' and would be in the same standing as you. what about having your credentials validated? you know, doing the necessary exams, filling out the forms and getting licensed? would that be a possibility? from years of dealing with undergraduates, i honestly don't believe most people take bachelor's degrees in psychology because they want to end up working in the area of mental health. as you probably know, a college degree has now become the new "high school diploma" in terms of potential employers expecting you to have a degree just to even be considered as a potential hire for something as basic as, i dunno, an executive assistant or a secretary? psychology just happens to be very popular... so a lot of students simply take it because its popular/interesting but are really focused on getting a job when they graduate (and any job will do). there is also the possibility of you becoming a research psychologist. you'll never work in mental health but you still need a degree in psychology to get into graduate school and do this. my graduate program, for instance, is geared towards Psychometrics/Data Analysis in the social sciences and most people have a Bachelor's or a Master's degree in Psychology. but we will never work on anything directly related to mental health. we're research-only people. so yeah... Psych has a very broad scope here and you may end up doing stuff that has absolutely nothing to do with people.

well, Counselling Psych and Social Work are usually a little more lenient in terms of their background so you could also consider those as possibilities?

it could, potentially. i tend to see these things as gambles (maybe it's my training as a statistician, who knows). you have a certain probability of rejection regardless of what your application looks like and, ideally, you would aim at reducing that probability. an important thing to keep in mind is that GRE scores tend to be evaluated contingent BOTH on the rest of your application and the applications of other candidates. nevertheless, it does seem that many successful applicants tend to gravitate towards higher scores. for instance, take a look at SFU's admission statistics (the most recent year is 2012 but i guess it helps make the point): http://www.psyc.sfu.ca/grad/index.php?topic=clin_progstats their program doesn't have a strict cut-off in terms of GRE scores, but it seems like the 80% mark pops up again (well, 78% for the quantitative portion). at the end of the day this is a numbers game because 100s of applicants are competing for a limited number of seats (like in that SFU website, out of 164 applications only 14 got in. that's less than 10% of applicants. and SFU isn't even very highly ranked among universities). will your higher marks in research methods courses help you? well, it depends on what other applicants bring to the table. because so many people are trying to get in, trivial differences like GRE scores could be magnified i think your research experience (and not necessarily your grades) is your strongest suit. have you published anything? or maybe done at least a conference/poster presentation? that stands out because it speaks to your ability to conduct research. can you potentially meet up with some of the profs you would like to work with? when i applied to my program i didn't think i would be able to get in because there were lots of things working against me (like i don’t' have an undergrad degree in Psychology). so i made sure the person i wanted to work with knew who i was... i met up with him, i went to presentations he gave, i sat in some of his classes, i hustled and bustled to make sure he would remember my name when he saw my application and it paid off. i knew my chances of acceptance were going to be hindered by my degree, inability to secure funding, etc. so i worked around with what i had to make sure i could compensate for it. you're in a similar case. your GRE is not the best it could be, but you can work with other things to make your application compensates for that. i tend to feel iffy about the grades stuff because most graduate programs already require their applicants to have top-notch grades in their research methods/statistics courses, so i'm not sure how's that gonna help you stand-out when they compare you with other applicants. and if your application looks exactly like candidate X's but candidate X has a better GRE score, it's much more likely that candidate X will be accepted instead of you. all in all i guess it really is up to you and how much of a gamble you're willing to make when you apply. (OR you could choose schools that don't ask for GRE scores! hopefully it will become a trend that catches on )

you sound competitive, although i guess this is contingent to the programs you're planning to apply? for instance, UBC's website specifies: All applicants should take both the General and the Subject components of the Graduate Record Exam (GRE). The General GRE is required and the Psychology subject-test GRE is recommended but not required. Tests must have been taken within the last five years. Scores on this exam are considered in evaluating the acceptability of an applicant. Successful applicants will normally score better than the 80th percentile. and you barely cracked the 40th percentile on the quantitative section. i guess if you're willing to be on the sure side (and if it's not too much of a hassle) giving it another try wouldn't hurt?

were you at least able to confirm whether or not the offer was only for the first year? i have to say it almost sounds like a cruel joke if it is. like "sure, we'll cover you for the first year... but after that.... YOU'RE ON YOUR OWN".

i don't think it's California only. recently there was a little bit of a brouhaha over here because of some pretty stringent reductions in budgets for international students (particularly in the humanities/social sciences area). we complained but nobody really cared. i guess now that universities operate like corporations we can expect to see some 'restructuring' every now and then? because one thing they did change was making it easier for self-funded students to pay things.

UBC (Vancouver) and UoT (Toronto) offer them as well, but i would definitely echo surefire's concern: they are pretty tough to get for international students because of the expense of the tuition and the limited positions available.

honestly, i'd be willing to bet my brownies that no GRE score, research experience, etc. can help you out more than good connections and knowing the right people in the right places.

as an (ex-) international student myself (and doing some research on admissions stuff), i'd say it's really more of a quick yes/no check. as in "can he/she communicate efficiently in English? -if yes, proceed to evaluate the application. if no, toss out". moody does have a point though (and i think it happens across universities) where if you're gonna TA, you do need to show proficiency beyond the bare minimum. still, i think if a person is seriously considering moving to the U.S./Canada for grad school, i'd assume said person knows that she/he can do better than "the bare minimum" in the TOEFL/IELTS.

what about something like a program in applied statistics/psychometrics from something like an education or a psychology department? it mixes and matches social sciences with a quantitative bent and with the increase in standardized testing across the world, we're an in-demand profession. i haven't even finished my PhD and i routinely get a few job offers every semester about positions related to this, particularly testing companies like ETS (you know, the guys who brought you the TOEFL, SAT, etc.) or universities to do some teaching in research methods. i sometimes even get emails from the same people because they go for months without qualified people applying! we happen to be a rare species with a rare set of skills. here's a list of programs from the APA website of universities (in the U.S.) who have this kind of program. there're also a few in Canada, but there aren't many (like only 3-4 in the biggest universities) http://www.apa.org/research/tools/quantitative/?item=5

i wrote a paragraph, read this and decided it pretty much summarized everything i had said. so... ditto that.

OH! i see. thanks for clarifying. then yes, i'd say getting into an MA in Canada would be the equivalent of getting into a PhD in the U.S, in terms of the onerous process. particularly because once you get in an MA is relatively straightforward to jump into a PhD. plus it's also pretty common for people to just keep on doing their PhD within the same program out of convenience more than anything else. since there are fewer universities in Canada people rarely switch universities from MA to PhD, particularly if you manage to get into a prestigious program there are plenty of opportunities for TAships/RAships at the MA level, so i wouldn't worry about that. on the other hand, there aren't many $$$ goodies unless you're a Canadian citizen/permanent resident. the few stuff that's out there for int'l students is really hard to get (unless you're in the natural sciences, they have it easier). i know for a fact that 2 prospective int'l students (actually one was American) decided against joining our lab because we couldn't offer them a lot of money (where by "a lot" i mean a livable stipend) well... what can i say about that. i go to UBC and i can't complain i guess i like pulling that every now and then because my allegiance to UBC prohibits me from saying nice stuff to our archenemies, the evil U. of Toronto and the villainous McGill U. XD

i think we'd need a little bit more clarification with what you mean by "on par". you mean on par that you'd be taking the same courses? on par in terms you'd be able to get a PhD-level job? on par in terms of whether you'd be getting paid the same? i guess i'd more tentatively answer it'd be on par with a master's program in the U.S., particularly because there's no way you can cram coursework, research and practicum in just 2 yrs. i think Dedi made it clear: you'd be an int'l student so you'd be competing with all the other int'l applicants. your tuition would be higher (i know this because i was an int'l student for most of my MA) which means you'll need more funding which means you'll need to get more grants, more applications and an overall more complicated process (unless you program fully covers your tuition). plus (and as a few of my American colleagues remind me every now and then when i see them at conferences): "why would we go to Canada if the best schools are here?" always keep in mind (a little out of date but still gets to the point): HA! it cracks me up every time XD

as far as UBC goes, yes to both of your questions. and i think more generally speaking (at least when i was researching programs) you get into the MA which is like your stepping ladder towards the PhD. you usually do all of your courses during the MA stage and do the bulk of your research/practicum hours as you start getting closer to the PhD. and you do get TAing/RAing opportunities at the MA stage. i know i did

i'd wait the semester out just to at least say you gave it a decent chance. when i started my MA program (also as an int'l student) i didn't really like the classes i was taking and questioned whether i was just wasting my time or not. but i found other interesting courses to take in other departments and that kept me going until i realized the program wasn't bad, it was just different from what i was used to. HOWEVER if you feel like you'll run out of money before the semester ends and have no foreseeable way to earn more i'd quit immediately.

i have to second the two people above me about how important it *IS* to contact your POIs. heck, even if you could meet them in person while maybe sitting in a class or something places a face in your application as opposed to some impersonal, anonymous piece of paper they're reading. i contacted my POI during an open talk he was giving and i made darn sure i made the best 1st impression i could so he would remember my name when i applied. and it paid off because now i'm his student

i think it's a great idea. but i also think it's an idea that, if pursued seriously, would probably suck up more time than you'd like. i'm a small (online) business owner and the opportunity to 'expand' my business presents itself every once in a while (at least once or twice per year). as you mentioned, i like the business because it frees me from the terror of tuition increases, stipend reductions, budget cuts, etc. that can happen at any given moment (and which i know deeply impact other grad students in my department) but when i look at my schedule and make a realistic assessment of my time, i realize that expanding the business necessarily translates into reducing the hours i have allocated for research/PhD work. and i like my research too much to sacrifice it for a better paycheque since i'ma already making decent money... but i still keep the business running on the side because if getting an academic job fails (which is highly likely but i still keep my hopes up) i can always do my business full-time and live off that. so my advice would be: great idea, but be ready to make sacrifices (particularly if you're just starting up) and these 'sacrifices' could be more costly than what you'd be willing to take on.