spunky

$1000 just to network? sounds pricey.... :/ have you googled around just to see whether people have opinions about this conference?

not really trolling but i can't help but always remember this scene every time i think about McGill and people, Bernard1992 is a troll. remember, DON'T FING. FEED. TROLLS

it would still be good if you could maybe tell us a little bit more about your research experience? like LebaneseKafta said, clinical/counselling PhD programs in Canada can be very, very competitive to get into so if you don't have maybe, a publication in a refereed journal or some professional conference presentations it wouldn't hurt you to take a year to improve in your research experience. but if you already have that, then applying straight to the PhD would make more sense.

( **giggidy)

i honestly feel like you'd need to narrow this down a little bit more. what would you like to do within Psychology? there are as many career options within Psychology as there are people studying it so without a more specific sense of what you're interested in, it's kind of hard to advice you

OH, well that changes things. but it sorta makes sense though... have you watched the Ivory Tower documentary? a few of the things they say are a little bit "out there" but one where they hit the nail on the head is when they make the case of the "for-profit" university model that is becoming so pervasive across North America. the crux of the issue is that unless you're part of a "brandname" university (e.g. Harvard, Standford, Yale, etc.) it makes economic sense for other universities to accept as many undergraduate students as they can as long as they come with a bag full of money to dump in the university... cue in the student debt crisis now.

omg, and everybody gets funding as well? like i do know of quite a few programs who willingly accept anyone as long as they're willing to pay from their own pocket.

from Wallace Stanley Sayre: "Academic politics is the most vicious and bitter form of politics, because the stakes are so low." after become acquainted with this corollary of what is commonly known as Sayre's Law i think i just stopped caring about academic politics altogether

well, the thing is that Quant Psych didn't appear as a separate, independent field until the 90s. like there were not many PhD programs uniquely specialized in Quant Psych so a lot of the early figures had PhDs in something else and then they became Quants. it's because of a report that came out in the 90s from APA or something about how lacking Psych was in its methods and the need to push for more advanced statistical techniques

YESHHH!!! that sound that you just heard is the door of opportunity cracking open... go run through it! save yourself!

well... did you notice that ini mini tiny little note on how the NSF (or any other federal agency) defines 'unemployment'? it's Footnote #4 here: http://www.nsf.gov/statistics/infbrief/nsf14310/(or in any other of their footnotes): Persons are classified as unemployed if they do not have a job, have actively looked for work in the prior 4 weeks, and are currently available for work. Which means: - if you have been looking for work for longer than 4 weeks at the time of the survey, you didn't get counted. - if you don't have a job but have stopped looking because you're discouraged/tired you don't get counted (<-- happens A LOT in post-recession economies) - if you're on some sort of disability or had a child or something, even though you still need a job then you also don't get counted. so i always tend to feel iffy about these unemployment statistics. plus, like <ian> said, we need focus on the much more pervasive and much harder to measure cousin of unemployment, UNDERemployment . right next to my apartment building there's this lady with an MA in School Psych serving tea in a fancy tea house. the NSF (or its Canadian equivalent) would not count her as 'unemployed' yet i'm willing to bet my brownies you don't need an MA to serve tea. and this is what i think most people are interested in knowing. i'm currently looking for the APA source where i found that more PhD earners in Psychology are part-time employed now that full-time employed, which i think tends to paint a better picture of these trends but i'm being unsuccessful overall, i do like the "cautiously optimistic" approach you preach. my grandma used to call it something like "prepare for the worst but hope for the best". there is at least ONE marketable skill that anyone with a PhD in Psychology can always bank on, regardless of the area: we know how to do research. now, research can take many shapes and forms, but we all have to learn at least the very basics of it and i think if anyone can focus on how to expand that into other more applied settings, then you do have at least a slight advantage over your average recent-college grad. if EVERTHING else fails peepz, just remember at least one thing: Jenna Marbles has a Master's Degree in Sports/Counselling Psych from BostonU and she's the 7th most-subscribed youtuber! if she can do it, so can you! put your degree to a good use!

this joke makes more sense if you've watched the last movie from "The Hobbit"

i think i would focus more on the statistical topics aspect of things and just tangentially mention that you also have substantive research interests and describe the ways in which you would like to apply the new methods you will learn to these other areas. that way you're conveying the idea that you're still committed to your quant knowledge as your core area of research. i just fear you could face the potential risk of an advisor reading over your statement and thinking "uhm... this sounds like a social psychologist who lost her/his way. better throw it in the 'no' pile just to be sure". keep in mind that just because not many people apply to these programs does it mean they let in anybody. my program, for example, rejected all applicants for 3 consecutive years before getting in their new cohort of students even though we rarely, if ever, receive more than 10 applications per year. in the long run that's a good thing because that means advisors are seating on piles of sweet sweet unused funding waiting to be spent we usually get around 5 or 6 applications from which only 1 or 2 people get an interview. on the bright side, you pretty much have the guarantee that your potential advisor will conscientiously read all of your application package for no reason other than it is not an insurmountable task. especially when you compare it with people who supervise social psych or clinical psych programs and get north of 300 applications every year.

well, i upvoted him/her because i do feel like he/she makes a valid point

what....what is this strange feeling? COMPETITION?

give me cookies.... .... OR GIVE ME DEATH!!! XD

I see… yeah, that could be the case. Do keep in mind, however, that the bulk of your research would be in quantitative methods and statistical developments but I don’t see any reason as why you shouldn’t be able to pair that up with more substantive research.

Well… uhm… to be honest, if you’re starting from “below ground zero” and don’t have an advisor to guide you through the process, I’m not sure how doable Option 1 would be for you (where Option 1 means working out some theoretical result). Usually, it does take some exposure to theoretical psychometrics or statistics to become acquainted with these types of problems and see how to go about solving them. From my experience, if something seems straightforward enough either people won’t care about it (because it’s too simple) or it’s not relevant enough. But here are some of the things in which I have (unsuccessfully) dabbled in, in case you want to take a shot at them: - Tenko Raykov has been the only person I know who was able to derive the exact bias of Cronbach alpha, in the population, when the data follows a congeneric 1-factor model (different loadings, different error variances). He leaves open the problem of deriving the bias for finite samples. You could try and work on it. - Ke-Hai Yuan (et.al.) derived a new definition, standard error and sampling distribution of Mardia’s multivariate kurtosis under data that is Missing Completely At Random (MCAR).There has been work (and I'm currently looking into it) to extend it to the more general case of Missing At Random (MAR) but the standard errors/sampling distribution has been much more difficult to derive than anticipated. You could try a shot at that. - Donald Zimmerman extended the axioms of Classical Test Theory to measure-theoretic Hilbert spaces. In order to accommodate for more flexible types of norming not restricted by the inner-products, my advisor and I have attempted to extend them to Banach spaces. We haven’t been able to… but you’re welcome to try If you want my opinion, I think Option 2 (a Monte Carlo simulation study) seems like a much more doable option if you’re mostly working on your own. You just need to become sufficiently proficient in statistics and R (or any other software but I’m R-biased LOL) and figure out how to program the right things there. There is A LOT of simulation work going on all the time and I feel like this is a problem that you could tackle. Option 3 I am conflicted about. In general, I don’t feel like Quant Psych peepz really see analyzing data with a fancy method like anything particularly worthwhile (unless it’s a devilish design or something) because it really only says “oh look! I know how to type the right commands of code!”. A twist that I would give it to make it more interesting is maybe looking for similar problems in finance or economics or physics and bringing in those methods into Psychology. For example, in the Journal of Behavioural Statistics someone suggested the use of a method apparently used in by particle physicists to analyze likert-type data and settle, once and for all, the debate on whether you should analyze this type of data with parametric or non-parametric methods. Big Data and Machine Learning algorithms are really hot right now so you could maybe try and data-mine some big Mental Health database or something… I could see people being interested in that. But in terms of what would get you published in a quant journal at this stage, I suggest Option 2. Although if you manage to solve any of the problems in Option 1 do let me know I really hope someone else who is in Quant Psych would chip in here. I feel like the people who read this thread are only getting my perspective of things and I’m sure people would benefit more if more perspectives were brought into the discussion.

That's entirely possible. The majority of people who apply to Quant Psych programs are psych undergrads who took both the intro and advanced research methods sequence and somehow (usually accidentally) end up finding about this area of psychology. I think it is desirable (but not mandatory) to have a solid foundation in math/stats beyond the intro and advanced research methods courses with the benefit of hindsight, comparing my experience with that of my peers who didn't have a solid math base. But I find it difficult to believe that any program would just outright reject someone because he or she didn't go through the college calculus sequence or something like that. Just be willing to work hard, have tons of fun and you'll be OK

Well… they sorta tried this before with the SATs back in the 60s during the “great score decline” with somewhat mixed results. I believe Roger’s book Social foundations of testing: A multicultural perspective mentions something about it. The main problem was they were not able to find enough items in which minorities/women/choose-your-group-of-choice outperformed white males to make any significant contributions to the total scores. Usually, if minorities/women/choose-your-group-of-choice performed well in a set of items, white men did so as well… although that was not the other way around and nobody could figure out why. It’s important to keep in mind that the ecological/contextualized paradigm of testing (also known as the “third generation” of testing) was just starting to gain traction so this baffled a lot of people in ETS and other testing companies. Eventually, they just decided to stop right there because they were about to open another massive can of worms had they gone further, opting instead for doing normed scores (the ones where your scores are calculated with reference to other people of similar demographic characteristics). I still feel, however, that the problem is not so much on the tests themselves but on the use the tests are given by profs/AdComs/university authorities.

This is definitely a big part of it. And if we’re all honest about it, we’ve done something similar before. Like how many times as an undergrad did you or anyone else go on ratemyprofessors just to see who gave away “easy As”? Or maybe decided to skip a particular course until another prof taught it? I mean, it happens even within universities where profs themselves don’t have the same standards of effort when it comes to grading. Now, if that happens within the micro cosmos of a university department, imagine just how much bigger the problem is across universities themselves? Even from a purely psychometric point of view, the question of standardization is not easy. People are simply too different to find that magic one-size-fits-all approach that the test is supposed to be. That’s why I do have to say that even with all its limitations, the GRE is kind of the least crappy thing we have that is still feasible . As I said, if we lived in the magical land of spunky’s awesomeness everything would be holistic examinations… but we don’t live in said place. Which is why, I guess, we can sort of try and do the best we can with what we have which is acknowledge that yes, maybe the GRE score should be something to consider but definitely not carry the weight that it carries. It was never designed to do the stuff people do with it… but it’s just too darn convenient to let it go!

Well, there is certainly room for the traditional lecture-style approach in these classes and I think that’s a very appropriate model of teaching in the beginning because… well, we all have to start somewhere, right? But then I try to make things as interesting and interactive as I can. For example: - I use the rgl package from R a lot to make pretty plots like this one here: https://www.youtube.com/watch?v=JaMgi4XBjo8 I realize that not many people have worked with 3D objects before and I can see it definitely helps people make the connections between simple and multiple linear regression. Also, the General Linear Model can be represented beautifully in terms of planes, vectors and angles. I have found that if you connect ANOVA and regression to their geometric analogues people somehow ‘get it’ more. And then I ask them questions like “what would you think it will happen if I add a lot of data points towards the middle of the regression plane? Will it move? Will it tilt? etc. People vote in their answers with a system like the clickers in undergrad and then I get an immediate impression of whether the whole class is on the same page or not. And because everything is in R I can code right on the spot whichever questions or doubts my students could have and visually demonstrate the answer - I do a lot of in-class group activities that help connect the interpretation of software output with research questions. Like I give them a research scenario and some SPSS or R output and let them come to conclusions of whether the output gives them the answer they want or if something is missing or, sometimes, I even give them output completely unrelated to the question and they can spot it right away! (I, of course, let them know in advance that this is a possibility). - There are some in-class discussions that have got me in some hot water before but I've found that students love them (and my advisor has my back on this). I like discussing with my students the methodology of published but poorly-designed articles. In order to make them interested I (purposefully) choose controversial subjects that will not sit well with my moderate-to-extremely liberal, non-religious, socialist-leaning crowd of students… so stuff that supposedly “shows” that children of gay parents are worse off than children of straight parents or articles that say certain ethnic group or gender is somehow inferior to others. But they key here (and I make that VERY clear from the beginning) is that I don’t want to hear any discussion about the theoretical standpoint of the authors or ethics or anything like that. It’s all about methods methods methods and only methods. Were their statistics done correctly? Do the conclusions from the analysis follow from the analysis itself? What kind of data did they gather? What kind of design did they use? Was the design suitable to the research question? I want to communicate to my students the power that being a good methodologist can convey. This is the one and only area where you can make or break any scientist’s theory or research without having to know anything about his/her area. You just need to look at their methods/analysis and if that’s flimsy, everything else collapses regardless of how much BS they want to throw at you. I believe once people realize that research methodology/statistics is just critical thinking on steroids they become much more aware of the importance of this seemingly dry and dull area has. The best compliment I ever got was that, towards the end of the semester, one student told me that after taking my class she felt like a door had opened inside her mind and now everything she did was question everything…. Hidden assumptions, bad data practice… it’s all everywhere! It’s almost like when Neo from The Matrix “wakes up” and he becomes able to see the computer code all around him… things become apparent for what they really are and not what they intend to be.