spunky

In my experience, psychological research tends to be pretty number-heavy, particularly if you’re aiming to publish in the top journals. The whole Crisis of Replicability brouhaha alongside with the movement towards Open Science and is placing a renewed emphasis on proper methodology and statistics. But it does not necessarily *have* to be. I mean, there are some pretty strong published papers out there where the statistics and number-crunching is not particularly complicated because they have very powerful research designs with strong protocols. In my experience, the sophistication of statistical analysis tends to be inversely related to the strength of the research design. The weaker your design, the more advanced the statistical analysis has to be to account for it. But the “mathematization” of psychology (and I guess the social sciences in general) has been going on for a while, particularly with the advent of cognitive psychology and neuroscience, which definitely pushed it forward.
If your emphasis is on clinical work more than research, however, I would say a moderate statistical background is at least necessary to be able to evaluate research papers and see whether the claims they make are substantiated or not. But I’d definitely say that, in those cases, you don’t need to be as proficient in statistics as if you were mostly a research psychologist. 
Still, though, there are programs (mostly in counselling psych, not so much in clinical) that prefer the more qualitative approach to research and the statistics part is kept at a minimum so that could be something to explore if math/stats is not your thing?

From what you described, I feel like your profile is pretty decent for a candidate applying to Quant Psych programs. Like I shared on my previous post (and quite a few other threads in this forum) this area is still “Psychology’s best kept secret” (that is changing fast though. I’ll elaborate further towards the end) so there isn’t really an expectation that any given candidate should be proficient in it. A traditional 4-year undergrad training in psychology usually gives you exposure to most of the major areas within psychology (social/personality, abnormal, clinical, etc.), but rarely do you get to learn anything about Quant Psych as an actual subfield of psychology, with a research programme beyond the mandatory research methods classes. Professors know this and I feel what they look for, more than anything, is just people who are enthusiastic about research methods or statistics and who have demonstrated to be numerically inclined (usually through good grades in stats classes, a good quant GRE and maybe some data analysis sample writing where you did something beyond a 1-way ANOVA or a multiple regression with 3-5 variables). With that being said, the more you can demonstrate you have training in Statistics, Mathematics and programming (programming being VERY important, especially in a statistical environment like R/SAS/STATA/etc.) the better your chances will be of impressing potential committee members. 
The fact that you’re RAing in a Quant Psych lab is priceless in itself. From what you describe, I feel that is your strongest selling point and it will make your application stand out. Even if your role is mostly observational, profs know that you’re simply not well-trained enough so early in your academic career to start making substantive contributions. But they see you’re being exposed to the field, the terminology, the methods being used, etc. and that is invaluable. The thing is, although it is true that we resemble Statisticians more than Psychologists, it is also true that the methods we use, the lingo in which we speak, the issues we concern ourselves with, etc. are almost exclusively the province on the social sciences.  Knowing some of this before you start graduate school so you can jump into the literature without having to google every 2nd technical term is very good, so kudos to you for doing that. In our Quant Psych lab we also have a few undergrads every now and then and it’s pretty standard for them to stay mostly quiet, taking notes while the rest of us do most of the substantive discussion. They key point here is that you’re showing interest and you’re ready to learn new stuff. 
Regarding competitiveness and size of the program here are my thoughts. Although we are not (and I’m sure will never reach) social/personality or clinical psych type numbers, the number of applicants *is* increasing (and doing so fast) every year, for multiple reasons. The most obvious one is simply that more people are going to college. Because of this, the value of an undergrad degree keeps on shrinking (like a bachelor’s degree today is the new high school diploma of 20-30 yrs ago) and more people need to get more and more credentials to position themselves in the job market. The second (and much more interesting) issue are the particularly exciting times we’re living in. First of all, ALL statistics/data analytics/etc. programs are experiencing a newfound popularity. Professor Xiao-Li Meng, the head of the Statistics Department at Harvard, has commented on this very often, noting that ever since the word “data science” became popular, most quantitative-anything university programs have experienced a boost in applicants. I mean, you hear how companies like Google or Facebook are interested in employees capable of making sense of large amounts of data and willing to pay six-figure salaries for it and you’re *obviously* gonna get people from all corners on the word trying to get a piece of that. So… yeah, there’s that incentive right there. The other exciting aspect that pertains mostly to Psychology is the Crisis of Replicability and the weird, “wandering through the wilderness” stage in which we find ourselves into. The Ioannidis article on Why Most Published Findings Are False became popular almost at the same time as Brian Nosek hit the world of social psychology showing that half of some of the most prominent findings in his field do not replicate. Psychology obviously enters in panic wondering when things went wrong while those of us who exist in the world statistics/research methods/data analysis start pointing to articles from the 70s and 80s that were heralding this type of crisis while being mostly ignored by the majority of substantive/applied researchers... until they couldn’t ignore us anymore. But now that the crisis took hold, psychology (and many social sciences) is looking to their methodologists in search for answers in terms of best data practices and proper ways to conduct analyses. And that pushes the demand for people trained in methodology/statistics and for people who may otherwise not consider themselves “number savvy” to become interested in our field… increasing its ranks. Now that whole situation opened a different other can of worms, of course. We’re in the 2nd phase of the p-value war now (mostly being fought on Twitter and Facebook) where you have people advocating to lower the p-value threshold from .05 to .005, Bayesians saying we should just get rid of the Neyman-Pearson paradigm altogether, older frequentists saying there is nothing wrong with .05 but we need to train people better… I dunno, it’s a mess. But a fun one, because it is the kind of mess where methodologists, statisticians and data analysis type people are sorting themselves out to make sure we can present a coherent message to applied researchers. 
So yeah, I foresee Quant Psych programs will steadily become more and more popular the deeper we go into this change of paradigm so at least you know you’re making the right choice by jumping in early. A few universities are either opening Quant Psych type programs or expanding them to tackle whatever changes come into be so enjoy the ride!

If I may offer some advice from the perspective of someone who already graduated and went on his first round of  job hunting, there is an edge from an academic job perspective to go for a quant psych program rather than an ed psych program with a measurement/psychometric focus. I found out (sadly, a little too late) that ed psych type departments have no problem hiring people coming either from ed psych depts or from  psych depts as long as the courses/research they did in quant psych overlaps with ed psych  (i.e. some emphasis on measurement or psychometrics). Psych depts, however, seem to be a lot less interested in hiring people coming exclusively from ed psych programs. 
The course materials and research in both programs are usually 99% similar but I guess it does make a difference to them from which dept you come from :/

If I may offer some advice from the perspective of someone who already graduated and went on his first round of  job hunting, there is an edge from an academic job perspective to go for a quant psych program rather than an ed psych program with a measurement/psychometric focus. I found out (sadly, a little too late) that ed psych type departments have no problem hiring people coming either from ed psych depts or from  psych depts as long as the courses/research they did in quant psych overlaps with ed psych  (i.e. some emphasis on measurement or psychometrics). Psych depts, however, seem to be a lot less interested in hiring people coming exclusively from ed psych programs. 
The course materials and research in both programs are usually 99% similar but I guess it does make a difference to them from which dept you come from :/

If I may offer some advice from the perspective of someone who already graduated and went on his first round of  job hunting, there is an edge from an academic job perspective to go for a quant psych program rather than an ed psych program with a measurement/psychometric focus. I found out (sadly, a little too late) that ed psych type departments have no problem hiring people coming either from ed psych depts or from  psych depts as long as the courses/research they did in quant psych overlaps with ed psych  (i.e. some emphasis on measurement or psychometrics). Psych depts, however, seem to be a lot less interested in hiring people coming exclusively from ed psych programs. 
The course materials and research in both programs are usually 99% similar but I guess it does make a difference to them from which dept you come from :/

Thank you @schenar. When I first encountered this area of Quant Psych (almost a decade ago) I felt really alone and almost like I had to re-invent the wheel all by myself every time. My undergrad profs didn’t know much about it, online resources were scarce, the field seemed rather obscure, etc... That’s why I’ve stuck around this forum. I realized that, although things have changed, a lot of newcomers in the field need some extra guidance that people in more “mainstream” areas of psych can get from almost anywhere. 
Depending on which area of Quant Psych you specialize on, you can be very technical or more applied. There are certain PhD programs (I think OSU and UCLA are good examples) where Quant Psych peeps take master’s level courses in Statistics and Mathematics so that, by the end of your PhD, you can also claim an MSc in Statistics. So whereas a Quant Psych degree wouldn’t automatically make you a “data scientist”, the work you’re doing can get you sufficiently close to it so that you might as well pass for one. After a few years being into this whole programming (mostly in R and Python) world, I’ve concluded it is very much like being an artist. You keep an active online presence with a portfolio (e.g. a webpage, a github account, etc.) and you show your chops there (share your code, blog about programming/data analysis stuff) and people eventually will find you out. If you prefer to go the industry route (which I’m personally considering at the moment), people won’t care whether or not your degree is in quantitative social sciences VS statistics as long as you can demonstrate (via your online presence) that you have what it takes.  
Being involved in an applied research project is the best thing to fish around for ideas on what to do research on that’s more methodological/theoretical. Every idea I’ve had comes from someone asking me a question about regression or ANOVA or SEM or the t-test or something like that and me taking that “seemingly simple” question and logically extending it to its natural consequences. I remember I once had an undergraduate student asking quite innocuously whether or not a 1-way ANOVA would let him compare as many group means as he wanted without inflating Type 1 error rate. “Sure” – I said - “that’s why we do ANOVA instead of multiple t-tests. That way we can compare an infinite number of….” And my voice started trailing off. Can we compare an infinite (not finitely large, that’s trivial to show), but actually infinite number of group means? (Spoiler alert: we can but, it depends). So what started off as your typical 3rd year bachelor's student question became a really cool theoretical investigation of the asymptotic properties of Analysis of Variance. You never know when inspiration’s gonna hit. 
In any case, good thing is that you’re still in time to make an interesting career before the field begins to experience saturation
 

I do not know if your application is average or not because "average" depends on who else is in the application pool. Like @_kita said, it is a game of numbers now. If you were at the top 1% of applicants and 1000 people applied, you could be at the bottom of the 10 most talented people for that year. That's the thing with rejections. You have no way of knowing whether you barely missed your chance this year or if it turns out that this year most people who applied had lots of publications in very prestigious journals and it all came down to GRE scores. 
I honestly feel like you should give it at least one more honest chance. Give the GRE everything you've got, maybe try to have another pub or a conference presentation and see how it goes. And if it doesn't end up happening I mean... you have a wife, you have your children, you have a home. No PhD is gonna come close that. 

From what you described, I feel like your profile is pretty decent for a candidate applying to Quant Psych programs. Like I shared on my previous post (and quite a few other threads in this forum) this area is still “Psychology’s best kept secret” (that is changing fast though. I’ll elaborate further towards the end) so there isn’t really an expectation that any given candidate should be proficient in it. A traditional 4-year undergrad training in psychology usually gives you exposure to most of the major areas within psychology (social/personality, abnormal, clinical, etc.), but rarely do you get to learn anything about Quant Psych as an actual subfield of psychology, with a research programme beyond the mandatory research methods classes. Professors know this and I feel what they look for, more than anything, is just people who are enthusiastic about research methods or statistics and who have demonstrated to be numerically inclined (usually through good grades in stats classes, a good quant GRE and maybe some data analysis sample writing where you did something beyond a 1-way ANOVA or a multiple regression with 3-5 variables). With that being said, the more you can demonstrate you have training in Statistics, Mathematics and programming (programming being VERY important, especially in a statistical environment like R/SAS/STATA/etc.) the better your chances will be of impressing potential committee members. 
The fact that you’re RAing in a Quant Psych lab is priceless in itself. From what you describe, I feel that is your strongest selling point and it will make your application stand out. Even if your role is mostly observational, profs know that you’re simply not well-trained enough so early in your academic career to start making substantive contributions. But they see you’re being exposed to the field, the terminology, the methods being used, etc. and that is invaluable. The thing is, although it is true that we resemble Statisticians more than Psychologists, it is also true that the methods we use, the lingo in which we speak, the issues we concern ourselves with, etc. are almost exclusively the province on the social sciences.  Knowing some of this before you start graduate school so you can jump into the literature without having to google every 2nd technical term is very good, so kudos to you for doing that. In our Quant Psych lab we also have a few undergrads every now and then and it’s pretty standard for them to stay mostly quiet, taking notes while the rest of us do most of the substantive discussion. They key point here is that you’re showing interest and you’re ready to learn new stuff. 
Regarding competitiveness and size of the program here are my thoughts. Although we are not (and I’m sure will never reach) social/personality or clinical psych type numbers, the number of applicants *is* increasing (and doing so fast) every year, for multiple reasons. The most obvious one is simply that more people are going to college. Because of this, the value of an undergrad degree keeps on shrinking (like a bachelor’s degree today is the new high school diploma of 20-30 yrs ago) and more people need to get more and more credentials to position themselves in the job market. The second (and much more interesting) issue are the particularly exciting times we’re living in. First of all, ALL statistics/data analytics/etc. programs are experiencing a newfound popularity. Professor Xiao-Li Meng, the head of the Statistics Department at Harvard, has commented on this very often, noting that ever since the word “data science” became popular, most quantitative-anything university programs have experienced a boost in applicants. I mean, you hear how companies like Google or Facebook are interested in employees capable of making sense of large amounts of data and willing to pay six-figure salaries for it and you’re *obviously* gonna get people from all corners on the word trying to get a piece of that. So… yeah, there’s that incentive right there. The other exciting aspect that pertains mostly to Psychology is the Crisis of Replicability and the weird, “wandering through the wilderness” stage in which we find ourselves into. The Ioannidis article on Why Most Published Findings Are False became popular almost at the same time as Brian Nosek hit the world of social psychology showing that half of some of the most prominent findings in his field do not replicate. Psychology obviously enters in panic wondering when things went wrong while those of us who exist in the world statistics/research methods/data analysis start pointing to articles from the 70s and 80s that were heralding this type of crisis while being mostly ignored by the majority of substantive/applied researchers... until they couldn’t ignore us anymore. But now that the crisis took hold, psychology (and many social sciences) is looking to their methodologists in search for answers in terms of best data practices and proper ways to conduct analyses. And that pushes the demand for people trained in methodology/statistics and for people who may otherwise not consider themselves “number savvy” to become interested in our field… increasing its ranks. Now that whole situation opened a different other can of worms, of course. We’re in the 2nd phase of the p-value war now (mostly being fought on Twitter and Facebook) where you have people advocating to lower the p-value threshold from .05 to .005, Bayesians saying we should just get rid of the Neyman-Pearson paradigm altogether, older frequentists saying there is nothing wrong with .05 but we need to train people better… I dunno, it’s a mess. But a fun one, because it is the kind of mess where methodologists, statisticians and data analysis type people are sorting themselves out to make sure we can present a coherent message to applied researchers. 
So yeah, I foresee Quant Psych programs will steadily become more and more popular the deeper we go into this change of paradigm so at least you know you’re making the right choice by jumping in early. A few universities are either opening Quant Psych type programs or expanding them to tackle whatever changes come into be so enjoy the ride!

I think you should be OK. I mean, most people don’t start Quant Psych programs with a strong technical background (Mathematics, Statistics, computer programming, etc.). With that being said, however, it’s important to focus on which courses are bringing down your GPA. Like, for instance, if your upper-level Statistics courses are also your lowest grades, it kind of begs the question of how well you can handle mathematical research and stuff like that.  Just some stuff to think about. 

Frankly jobs are so hard to get and there are SO many factors beyond getting the "best" candidate for the job (whatever that means) that go into making a hiring decision, that I would not hesitate to utilize any advantage given to me. Keep in mind that once you're hired, no one is going to know what box you did or did not tick in some form, so if someone wants to think you were only hired because you are a minority, they will go ahead and think that and nothing you can say or do will change that. Since you're dealing with the disadvantages that come with that status, why not make use of the tools they have in place to even the playing field? (disclaimer: not that I am all that sure that that legalese and those forms actually do anything.. but you never know.)

Definitely do it. I can't speak so much for the situation in Canada, but it's typical for diversity to be ranked extremely high in importance at my current school. For one, if the pool is not diverse enough (or not enough people identify as diverse), it's not atypical for the search to be cancelled and re-advertised. For another, generally, if there are two relatively equally qualified people, preference for a hire will likely to go to the person with demonstrated diversity. 

@spunky, my experience has been that the HR forms about disability and diversity aren't actually accessible to the hiring committee (at least not in the USA). Personally, I'd say fill out the forms honestly. Also, in all honesty, there are many other ways for people to learn about your background and see whether or not you're diverse (e.g., have you ever won a diversity award? Are you active in organizations for women in science, first gen students, etc.?) by looking at your CV and experiences.
Tenure-track job ads in one of my fields for next year have started trickling out. I'm looking forward to largely being able to ignore them for once.

So after some of the recent discussion elsewhere on the board, I thought it might be nice to start an (admittedly early) job market support thread for those of us going on (or back on) the market in this upcoming cycle. 
For people on for the first time, I thought it might be nice to start early as a place to ask questions as you're preparing materials, and give those of us on for multiple years a place to commiserate and soothe our souls by helping someone else out. 
Since we have such a relatively small group of people at this stage, lets start with a combined thread for all of our woes, and can split it into disciplines if we want at a later date if the crowd grows enough. From conversations with friends, the application process isn't so different that there isn't a ton of overlap. 

hey! thanks for your post! could you please answer these questions as effectively as you can so that the best answer may be given?
* what are your goals?
* what exactly is your question?
* what exactly is the problem?
* what are the facts i should know?
* what research have you done so far on your question?
 
remember to bold anything important -- like your question

Thanks for the advice, but it's pretty clear (to me at least) that I've found all the information I need. 

Cheers!

I’ve always thought that becoming acquainted with the literature in your area is always the first step to develop your research interests and hopefully, by the end of graduate school, a research program.
 
Now that takes time, though. I have 11 folders with potential PhD dissertation topics that I left unfinished (maybe I’ll start working on them in the future, who knows) before I found “the one”. And I think “the one” usually comes with a question from you or some sort of realization that there’s this area that has gone vastly unexplored or maybe people are looking into it but you have a different idea of how to go about it. Like, you say there are many areas in your field that you find interesting. Pick maybe a few of those many and ask yourself a question that you’re interested in. See who has looked into this and how. Then try making it more specific and keep going until you find an area for you to start doing research and develop. If by the time you’ve got to that level of specificity you no longer find the area compelling or it’s become plain boring, then maybe move on to the next.
 
I honestly feel the majority of us go at this via trial-and-error so I wouldn’t be too worried about not having very defined research interests at this stage.

It is, actually. It's a joint Quantitative Psychology/Educational Measurement program. I'm very close to graduating so I started comparing my CV with the CVs of people I knew that had gone on to obtain tenure-track positions and the first thing I noticed was that by the time they had graduated they had A LOT more stuff on their CV than what I have on mine right now

Uhm... any reason of why you didn't consider publishing them? Or polishing them a little before publishing them?
I mean, I kind of feel someone could very well stumble on your blog, read one of your papers and think "oh wow, that's a good idea. I think I'll do a better version of it and publish it!" 

Uhm... any reason of why you didn't consider publishing them? Or polishing them a little before publishing them?
I mean, I kind of feel someone could very well stumble on your blog, read one of your papers and think "oh wow, that's a good idea. I think I'll do a better version of it and publish it!" 

We have something similar in our department. We use it mostly to try and gauge how many introductory statistics courses (and of which type) will be needed once the new student cohort begins its semester.

Because people come to grad school with somewhat different backgrounds in terms of their methodological training (I’ve seen everything from people having introductory grad-level courses in their transcripts as undergrads to the ones who barely passed intro to research methods) something like a quick practice test/interview helps us know the overall level from which people are starting from to plan ahead in terms of the courses they’ll need.

I really don’t think this is anything to worry about as far as whether or not they’ll like rescind your invitation to their program or anything.

Hello! Sure, I would be happy to help. I am a 3rd-year PhD student (graduating within a few months, actually) and I work both in a Quant Psych lab and an Educational Measurement one, so I tend to see how things are done in both types of programs. Honestly believe you may benefit by looking a little into Educational Measurement programs as well.
Lemme address each one of your questions one-by-one and I’ll post everything in the forum so other people can benefit from them. I kind of feel like Quant Psych is “psychology’s best public secret” because, although it is a very interesting and fun area to be in (with lots of opportunities for growth and employment both inside and outside academia) there is little info about this area out there and its number of PhD graduates still remains quite low (at least per stats in North American programs). The Crisis of Replicability has been shining the spotlight on us a little bit (particularly because we, as methodologists/statisticians, have been forecasting this crisis for about 30yrs or more) so let’s see how things change in the future. In any case….
My big question to you, is what can I do to improve my application beyond the basic have a good GRE, good GPA, etc.? I am not applying for programs until the Fall of 2017.
 
For this question the advice is somewhat standard. Find a lab where you can gain research experience and volunteer. Ideally, a Quant Psych lab would be the best one so you can directly look into what goes in the daily research life of people in these types of programs. Quantitative Psychology can also be very mathematical so it wouldn’t hurt if you have taken Mathematics/Statistics classes outside of Psychology. I place emphasis on outside because, in my experience, courses in research methods/statistics for social scientists are a tad bit skimpy on the theory behind the methods and you want to learn how to do these things beyond the “cookbook” level. I mean, it’s not super necessary but it’s gonna look good on your application.
I spoke with a Quantitative professor that offered to teach me R in an independent study. Is that a good idea?
 
It’s more than a good idea… I’d say you’re probably gonna be expected to know some R, SAS, STATA or some other programming environment by the time to apply. But R is very powerful and popular so I would place the bulk of my efforts on learning R. I mean, you can apply without knowing any of this but then you’re gonna be stuck with both having to learn how to program while taking classes, undergoing research, etc. You’re also not going to look as good on your application package when compared with people who already know R. At this level, SPSS is just not gonna cut it anymore so don’t forget everything you know but be prepared to rarely use SPSS ever again. I think I haven’t used SPSS in more like 2 or 3 years? Everything I do is in R. So yes, the faster you can learn R, the better.
The other software I would recommend you to become familiar with is MPLUS because that is the default now on latent variable modeling. R can do a lot of what MPLUS can, but people just use it a lot so knowing MPLUS syntax will let you communicate with other people who don’t use R. It wouldn’t hurt you to learn about other programming languages and have some idea of how to do database management (SQL) or data-visualization (Tableau), but this is really not as necessary.
The one thing that you *should* start becoming familiar with is how to code Monte Carlo simulations. Your research as a Quant Psych person happens primarily inside the computer and simulations are our bread and butter. You are gonna end up running A LOT of those so try to become familiar with the basic structure of for() and while() loops, how to optimize computer time and (if you use R) the family of apply() functions. A book I recommend first year students to get themselves started with is this one:
https://us.sagepub.com/en-us/nam/monte-carlo-simulation-and-resampling-methods-for-social-science/book241131
so if you can at least start going through some of the chapters and try to reproduce some of the examples it would place you ahead of most people by the time you begin.
I’ll admit I don’t have a calculus background beyond Calc I, but I do have a course on multivariate statistics. Do you think this will be a problem?
 
Not really, but then again it depends on what your ultimate goal is. Most people (like yourself) find this field by accident so almost everyone who applies starts off without a strong base of Mathematics/Statistics. You will learn most of what you need as you go but the downside is that (a) you will only know things at an “intuitive” level that does not necessarily generalize to the wider types of data you will encounter and (b) you may not be able to read and use the literature produced by and for Quantitative Psychologists. The primary journal of our field is Psychometrika. It is the most prestigious place to publish and what most people aim for. But, to be honest, without at least some notions of calculus, linear algebra and mathematical statistics most people can’t make it past the first two pages or so of any given article. So, would this be a problem to get in? No, I don’t think so. But it can end up becoming a problem in the future.
As a curious side-note, I did my BSc in Mathematics with some hints of Psychology and I found it somewhat peculiar that, when I was having my interview, my advisor had highlighted all the Math courses I took and basically ignored anything related to Psychology. The interview also went into that direction and I feel the reason for that is because very few people with background in Math/Stats/CompSci etc. wander into Quant Psych so whenever that happens, advisors are very happy to snatch you from the get-go. Your application does stand over other people’s if you can palpably demonstrate some sort of technical expertise (where technical means theoretical math or an ability to code).
Is there anything that applicants say/do that is specifically a deal breaker in quant programs?
 
Uhm… not that I’m aware of? Just make sure you don’t show your preference for Bayesian statistics in front of a frequentist professor (<--- HOHOHOHO I’m so clever… Am I not? Anyone? OK, I’ll let myself out now… :D). Although this may tie in with another question of yours which is…
I am not particularly interested in creating new statistical methods myself. I am more interested in tackling other people's data and looking into multi-level modeling. Is that a problem?
 
For the most part, yes. This will become a problem for you sooner or later. And the reason it will become a problem is because you’re aiming at doing the most basic implementation (i.e. data analysis) of what Quantitative Psychology has to offer. It is also a problem because, in reality, any skilled social/ clinical/personality/insert-your-area-of-choice psychologist can do the same thing. As a Quant Psych your selling point is something like “not only can I do data analysis. I can do data analysis, I can create new methods for data analysis and I can evaluate data analysis methods”. If you stop at the “I just want to do data analysis” well, that’s not gonna get you very far. And that is something that in my opinion (and from talking to other people in my area in conferences and whatnot) would be a deal-breaker if you’re trying to get into a program. I mean, think about it… from the get-go, you’re already signalling that you’re not interested in doing what most of us in the field are doing so the immediate question that pops up is “is this person even supposed to be here?”.
If you’re mostly focused on data analysis over research on statistic and theoretical psychometrics then I would encourage you to apply into a more substantive program (social/clinical/personality/etc.) and just either do a minor in Quant Psych or take as many statistics/methods courses as you can. The fact of the matter is that a Quant Psych PhD program looks more like a watered-down Statistics PhD program (with a few exceptions, Ohio State comes to mind) than a Psychology program. You’ll find out soon enough that most of your research happens inside the digital bowels of a computer and not so much going out in the field and talking to real people. I mean, you do some of that but that’s definitely not what your training as a Quant Psych will do for you.
Is a Quantitative psychology PhD program a good place for someone particularly interested in measurement of personality and psychological disorders?
 
You can do that but if what you are really looking for is the measurement aspect of things and not necessarily the statistical aspect, a program in Educational Measurement might be a better fit for you. In my assessment, Quantitative Psychology programs are more programs in Statistics with some Psychometrics thrown into them, whereas Educational Measurement programs are more programs in Psychometrics with some Statistics thrown into the mix. I do find that Educational Measurement programs tackle some interesting aspects of scale construction and development (like how to create norms, psychometrically-sound ways to score tests, etc.) that do not necessarily make it into Quant Psych. And the reason behind this is Item Response Theory, IRT. Educational Measurement programs have been, for the most part, the bastion of IRT because the sample sizes you need to run these models accurately can easily go into the 1000s. And, at least form my experience, your standard Psychology research sample size is somewhere in the low 100s. Plus Educational Measurement programs place heavy emphasis on what happens outside the context of data analysis (The Standards for Educational and Psychological Testing will become your new go-to book for everything) whereas I  feel like Quant Psych programs place a lot more emphasis on the data analysis part itself.
 
 
Now, again, this is just a wide scope, generalization of how Quant Psych and Educational Measurement works. I’m sure if you look hard enough, you may find the one program with that one faculty member that does exactly what you want to do. But from the type of questions that you’re asking, I’m wondering whether Quant Psych is actually the right fit for you and if you may be better off in another program and just being very studious with your methods. Or perhaps an Educational Measurement program, have you looked into those? I feel the faculty in those programs is a little bit more diverse as far as research interests go. Another thing I would recommend you to do is to grab maybe some of the high impact journals in the field and have a look at what kind of research they publish. When you have the time, look into these 3 journals: Psychometrika, Multivariate Behavioural Research and the British Journal of Mathematical and Statistical Psychology. Go through the most recent issues, see the kind of stuff that gets published there and ask yourself: “is this the kind of research I would like to do for the rest of my professional career?” if your answer is “yes”, then Quant Psych is definitely your field. If your answer is “no” then… well, I think looking at other options might be worthwhile.

Well, there are other ways (aside from increasing the number of quantitative psychologists) and many of them have already been put in place. Given the relevance that publishing has in academia, journal editors can have a lot of influence in shaping the way in which analyses are carried on and results are presented. For instance, during last year’s annual meeting of the Society for Personality and Social Psychology, Dr. Simine Vazire detailed some of the new policies and practices regarding data analysis/methodology that are being enacted in the journals where she serves as an editor in order to improve the quality of manuscripts they receive. Statcheck, in spite of its controversy, is becoming very popular very quickly for editors to automatically check whether or not the reporting of statistics in APA-formatted journals was done right. And I do know for a fact that this is being used by journals because I’ve been contacted by professors in the past asking me about these rather cryptic emails they get regarding whether or not they had "passed" or "failed" Statcheck.
There aren’t many quantitative-type psychologists, when compared to the more mainstream subfields like clinical or social/personality, that is definitely true. But this situation is also changing. The relevance that data has in society both inside and outside academia (that buzzword “big data” comes to mind) has definitely brought in a renewed interest in statistics or this new thing, “data science”. SAGE Publishing just conducted a study last year (in which I participated) regarding the role that big data will play now in psychology and the social sciences. They’re supposedly preparing a journal devoted entirely to this. Combine this excitement about data with the change in paradigm that the Crisis of Replicability is bringing about, and I truly thing it’s just a matter of time before statistics/methodology starts playing a more central role in the formation of academic psychologists. Heck, even in this forum I have seen the change. When I first joined, we barely ever had any questions related to Quant Psych/psychometrics. And now I’m pretty sure this is the first time ever we’ve actually had a quant psych applicants’ thread! I’m sure that this change will not happen overnight (although who knows, some exciting stuff is happening very quickly like the OP mentioned in the beginning) but I do think it’s coming. We need it.  

We have something similar in our department. We use it mostly to try and gauge how many introductory statistics courses (and of which type) will be needed once the new student cohort begins its semester.

Because people come to grad school with somewhat different backgrounds in terms of their methodological training (I’ve seen everything from people having introductory grad-level courses in their transcripts as undergrads to the ones who barely passed intro to research methods) something like a quick practice test/interview helps us know the overall level from which people are starting from to plan ahead in terms of the courses they’ll need.

I really don’t think this is anything to worry about as far as whether or not they’ll like rescind your invitation to their program or anything.

Hello! Sure, I would be happy to help. I am a 3rd-year PhD student (graduating within a few months, actually) and I work both in a Quant Psych lab and an Educational Measurement one, so I tend to see how things are done in both types of programs. Honestly believe you may benefit by looking a little into Educational Measurement programs as well.
Lemme address each one of your questions one-by-one and I’ll post everything in the forum so other people can benefit from them. I kind of feel like Quant Psych is “psychology’s best public secret” because, although it is a very interesting and fun area to be in (with lots of opportunities for growth and employment both inside and outside academia) there is little info about this area out there and its number of PhD graduates still remains quite low (at least per stats in North American programs). The Crisis of Replicability has been shining the spotlight on us a little bit (particularly because we, as methodologists/statisticians, have been forecasting this crisis for about 30yrs or more) so let’s see how things change in the future. In any case….
My big question to you, is what can I do to improve my application beyond the basic have a good GRE, good GPA, etc.? I am not applying for programs until the Fall of 2017.
 
For this question the advice is somewhat standard. Find a lab where you can gain research experience and volunteer. Ideally, a Quant Psych lab would be the best one so you can directly look into what goes in the daily research life of people in these types of programs. Quantitative Psychology can also be very mathematical so it wouldn’t hurt if you have taken Mathematics/Statistics classes outside of Psychology. I place emphasis on outside because, in my experience, courses in research methods/statistics for social scientists are a tad bit skimpy on the theory behind the methods and you want to learn how to do these things beyond the “cookbook” level. I mean, it’s not super necessary but it’s gonna look good on your application.
I spoke with a Quantitative professor that offered to teach me R in an independent study. Is that a good idea?
 
It’s more than a good idea… I’d say you’re probably gonna be expected to know some R, SAS, STATA or some other programming environment by the time to apply. But R is very powerful and popular so I would place the bulk of my efforts on learning R. I mean, you can apply without knowing any of this but then you’re gonna be stuck with both having to learn how to program while taking classes, undergoing research, etc. You’re also not going to look as good on your application package when compared with people who already know R. At this level, SPSS is just not gonna cut it anymore so don’t forget everything you know but be prepared to rarely use SPSS ever again. I think I haven’t used SPSS in more like 2 or 3 years? Everything I do is in R. So yes, the faster you can learn R, the better.
The other software I would recommend you to become familiar with is MPLUS because that is the default now on latent variable modeling. R can do a lot of what MPLUS can, but people just use it a lot so knowing MPLUS syntax will let you communicate with other people who don’t use R. It wouldn’t hurt you to learn about other programming languages and have some idea of how to do database management (SQL) or data-visualization (Tableau), but this is really not as necessary.
The one thing that you *should* start becoming familiar with is how to code Monte Carlo simulations. Your research as a Quant Psych person happens primarily inside the computer and simulations are our bread and butter. You are gonna end up running A LOT of those so try to become familiar with the basic structure of for() and while() loops, how to optimize computer time and (if you use R) the family of apply() functions. A book I recommend first year students to get themselves started with is this one:
https://us.sagepub.com/en-us/nam/monte-carlo-simulation-and-resampling-methods-for-social-science/book241131
so if you can at least start going through some of the chapters and try to reproduce some of the examples it would place you ahead of most people by the time you begin.
I’ll admit I don’t have a calculus background beyond Calc I, but I do have a course on multivariate statistics. Do you think this will be a problem?
 
Not really, but then again it depends on what your ultimate goal is. Most people (like yourself) find this field by accident so almost everyone who applies starts off without a strong base of Mathematics/Statistics. You will learn most of what you need as you go but the downside is that (a) you will only know things at an “intuitive” level that does not necessarily generalize to the wider types of data you will encounter and (b) you may not be able to read and use the literature produced by and for Quantitative Psychologists. The primary journal of our field is Psychometrika. It is the most prestigious place to publish and what most people aim for. But, to be honest, without at least some notions of calculus, linear algebra and mathematical statistics most people can’t make it past the first two pages or so of any given article. So, would this be a problem to get in? No, I don’t think so. But it can end up becoming a problem in the future.
As a curious side-note, I did my BSc in Mathematics with some hints of Psychology and I found it somewhat peculiar that, when I was having my interview, my advisor had highlighted all the Math courses I took and basically ignored anything related to Psychology. The interview also went into that direction and I feel the reason for that is because very few people with background in Math/Stats/CompSci etc. wander into Quant Psych so whenever that happens, advisors are very happy to snatch you from the get-go. Your application does stand over other people’s if you can palpably demonstrate some sort of technical expertise (where technical means theoretical math or an ability to code).
Is there anything that applicants say/do that is specifically a deal breaker in quant programs?
 
Uhm… not that I’m aware of? Just make sure you don’t show your preference for Bayesian statistics in front of a frequentist professor (<--- HOHOHOHO I’m so clever… Am I not? Anyone? OK, I’ll let myself out now… :D). Although this may tie in with another question of yours which is…
I am not particularly interested in creating new statistical methods myself. I am more interested in tackling other people's data and looking into multi-level modeling. Is that a problem?
 
For the most part, yes. This will become a problem for you sooner or later. And the reason it will become a problem is because you’re aiming at doing the most basic implementation (i.e. data analysis) of what Quantitative Psychology has to offer. It is also a problem because, in reality, any skilled social/ clinical/personality/insert-your-area-of-choice psychologist can do the same thing. As a Quant Psych your selling point is something like “not only can I do data analysis. I can do data analysis, I can create new methods for data analysis and I can evaluate data analysis methods”. If you stop at the “I just want to do data analysis” well, that’s not gonna get you very far. And that is something that in my opinion (and from talking to other people in my area in conferences and whatnot) would be a deal-breaker if you’re trying to get into a program. I mean, think about it… from the get-go, you’re already signalling that you’re not interested in doing what most of us in the field are doing so the immediate question that pops up is “is this person even supposed to be here?”.
If you’re mostly focused on data analysis over research on statistic and theoretical psychometrics then I would encourage you to apply into a more substantive program (social/clinical/personality/etc.) and just either do a minor in Quant Psych or take as many statistics/methods courses as you can. The fact of the matter is that a Quant Psych PhD program looks more like a watered-down Statistics PhD program (with a few exceptions, Ohio State comes to mind) than a Psychology program. You’ll find out soon enough that most of your research happens inside the digital bowels of a computer and not so much going out in the field and talking to real people. I mean, you do some of that but that’s definitely not what your training as a Quant Psych will do for you.
Is a Quantitative psychology PhD program a good place for someone particularly interested in measurement of personality and psychological disorders?
 
You can do that but if what you are really looking for is the measurement aspect of things and not necessarily the statistical aspect, a program in Educational Measurement might be a better fit for you. In my assessment, Quantitative Psychology programs are more programs in Statistics with some Psychometrics thrown into them, whereas Educational Measurement programs are more programs in Psychometrics with some Statistics thrown into the mix. I do find that Educational Measurement programs tackle some interesting aspects of scale construction and development (like how to create norms, psychometrically-sound ways to score tests, etc.) that do not necessarily make it into Quant Psych. And the reason behind this is Item Response Theory, IRT. Educational Measurement programs have been, for the most part, the bastion of IRT because the sample sizes you need to run these models accurately can easily go into the 1000s. And, at least form my experience, your standard Psychology research sample size is somewhere in the low 100s. Plus Educational Measurement programs place heavy emphasis on what happens outside the context of data analysis (The Standards for Educational and Psychological Testing will become your new go-to book for everything) whereas I  feel like Quant Psych programs place a lot more emphasis on the data analysis part itself.
 
 
Now, again, this is just a wide scope, generalization of how Quant Psych and Educational Measurement works. I’m sure if you look hard enough, you may find the one program with that one faculty member that does exactly what you want to do. But from the type of questions that you’re asking, I’m wondering whether Quant Psych is actually the right fit for you and if you may be better off in another program and just being very studious with your methods. Or perhaps an Educational Measurement program, have you looked into those? I feel the faculty in those programs is a little bit more diverse as far as research interests go. Another thing I would recommend you to do is to grab maybe some of the high impact journals in the field and have a look at what kind of research they publish. When you have the time, look into these 3 journals: Psychometrika, Multivariate Behavioural Research and the British Journal of Mathematical and Statistical Psychology. Go through the most recent issues, see the kind of stuff that gets published there and ask yourself: “is this the kind of research I would like to do for the rest of my professional career?” if your answer is “yes”, then Quant Psych is definitely your field. If your answer is “no” then… well, I think looking at other options might be worthwhile.

Your post kind of reminds me of a famous quote of physicist Max Planck related to the progress of scientific knowledge:
“A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it.”  
For the case of psychology I find this to be particularly tricky because, like Thomas Leahy pointed out in his classic book A History of Psychology, psychology (like most social sciences) advances horizontally as opposed to vertically. His argument kind of goes like this: in physics, math, chemistry, etc. you start with a theory, say the motion of objects as described by Aristotle. At some point what Aristotle had to offer was no longer enough (and many things were wrong) so whatever was useful of his theories remained and along came Newton with classic mechanics. Then Newton’s laws were not enough, physics kept what it needed from it and then Einstein and relativity comes along… and the processes continues on and on. Think about what happened in psychology. Leaving aside Wundt and the psychophysics people, say we start with the dominant theory of psychoanalysis. Then at some point there comes a certain Skinner and Watson and whatnot, tears it all down and starts with his own separate theory, behaviourism. Then came Rogers and the humanist bunch… and the cognitive-behavioural people… etc. etc. Not all the theories are completely mutually-exclusive but they are sufficiently different from one another that any one person can, at one point or another, identify with a particular school and keep on building it further. So whereas you can’t really apply to a Physics Dept and say you exclusively ascribe to the Aristotelian laws of physics because there really is just one big tower of physics, you can definitely apply to any of the many condos of psychology and keep on developing their theories and methods further.
 
Will the psychodynamic approach eventually die out? I guess so. But it will probably happen at such a slow rate that we will not see it within our lifetimes. I do hope that the biological model of behaviour and brain function eventually triumphs over all others, but my own experience helping out with research in these area has let me down a little bit. There is just SO much that needs to be discovered and cleaned up before we can even have a solid account of the neuroscience of behaviour that, again, I’m not sure if we’ll ever see direct applications of this in our lifetimes in the form of a well thought-out body of knowledge capable of overarching and encompassing predictions.
I do think it is a somewhat archaic way of thinking but I also don’t think the way psychodynamic theories are taught and applied today have a lot  of the original ways in which Freud thought about behaviour. I mean, they do have changed in the light of evidence and I’d like to believe that most clinicians, regardless of their theoretical bent, keep up with their research and re willing to change their practice depending on the evidence they see published.
Not so sure what programming ability and computer skills have to do with actual clinical practice in this setting though. I mean, I guess it’s cool if therapists also know how to program but as far as whether this type of training is relevant to their therapeutic experience… well…