MathStat86

Hi LostLamb, These are all great questions, and I'm interested in hearing the perspectives of others. In general, the answers to your questions are all "it depends on the program and advisor". Programs range very widely in terms of the mathematical rigor, some programs leaning strongly towards the "psychology" side, with classes that need to be accessible to the full psychology department and encouraging quant psych students to become involved in applied research with others in the applied area of the department, and some programs lean strongly towards the "quantitative" side. 1. The level of mathematical rigor: In terms of admissions: I've seen students accepted into programs from very different backgrounds and math preparations (when I was accepted into my program, I had a masters in math/stats... and the other girl that got accepted into my program had a stats minor in undergrad, I think she had taken Calc 1, but her experience was mostly in applied research). If you've worked with derivations and epsilon-delta proofs, your math background seems fine. In terms of the courses taken during the program: it differs a lot by programs. A lot of quant psych programs are housed in psychology departments and need to be accessible to the other psychology branches (clinical, social, etc.), whose math background may be as little as a class or two in college algebra. So the mathematical rigor in these classes is minimal (for someone who's taken so many math classes as you say), unless you are taking additional classes from the math/stats department. In terms of research: depends on the advisor. The people that I've worked with do simulation work mostly. Psychometrika is a more technical journal, so if you're looking to working with someone technical, I'd find professors that publish there. SEM and MBR are generally on the less technical side. PIs and programs, like you've pointed out, vary greatly in terms of where they stand on the spectrum between "mostly applied" to "extremely technical" work. Reading through some of their publications will probably tell you where they stand. From what you mention, it seems like you're doing that already, and that with you're background you're probably understanding a lot of the papers. 2. My answer to this question mirrors my answer in (1). Most accepted applicants from the last couple of years that I know have less background than what you're mentioning, but it ranges a lot. 4. Yes, previous experience with substantive research does help a lot. Since great part of quant psych is about bridging the gap between psych (applied) and stats, we value people in the middle who are quantitatively oriented but can communicate with psychologists and have a passion for psychology. If there is no interest in psychology, then a pure stats program would be more appropriate. So yes, especially since your background seems to be so strong on the mathematical side, I think it is important to highlight as well that you are interested and have worked with psych applied research. 6. It's program specific. Some programs encourage students to get a masters in stats along the way, and other programs do not offer the option to get a masters in stats. If this is something you're interested in, you can find out through the program's website, looking from alumni CVs, or directly contacting people that are in the program already. In my experience, most students are happy to answer questions (we are a small community and get very happy when we find out people are interested in our field).

I agree 100% with MissData and xolxs, and in fact I had started writing a response almost identical to xolxs before I saw it posted. My only addition is regarding research interests during the process of application, coming from a place where I had a very strong mathematical and statistical background, but no exposure whatsoever to the quant psych field or research. Before applying to programs, I spent about 2-3 weeks reading through many programs' websites and professors' research interests, trying to understand the type of research that they did. Although at first it might seem overwhelming, after some time you start to see common topics coming up repeatedly, themes, and understanding the types of questions that people in this field are trying to answer. For instance, some people focus on methods related to the development of psychological/educational assessments (for instance, how to make sure that the assessments accurately measure what they are supposed to), methods for longitudinal data (for instance, how to identify groups of people that follow similar developmental trajectories, or how to deal with missing data which is common in longitudinal studies), methods for non-randomized research designs (for instance, how to compare the effect of an intervention on groups of people who are different to begin with). These are just some (and somewhat simplified) examples. Reading papers from the potential PIs can be very challenging (the papers are sometimes very technical and difficult to understand), but it gives you a better idea of the types of questions that they are trying to answer and what you would be doing if you entered the field. I think this is an important part of the application process, because it really challenges you to think about what you want to do. Like the others already mentioned, nobody expects you to show up to an interview with a research proposal, but it's important to start thinking of what types of questions you want to answer with your research (and if your research interests change once you start a program, that's fine as well; that's very common).

Hello everyone, I am a quant psych student currently in my dissertation (last) year. When I applied to schools, I applied to 10 programs (among them were UCLA, UNC, ASU, Notre Dame, UVA, Missouri; a few others) and got into 9 of them. My background when I was applying was both in psychology and math/stats. I had a MA in Psychology and a MS in math with concentration in stats, both from a relatively small university. At the time, my thesis project during my MS in math/stats was what best prepared me to understand the field (and it was very helpful during interviewing). For my thesis I was doing a small simulation study testing different ways to handle missing data. Other than that, when I applied, I had no publications, no knowledge of the PhD lifestyle, and I had never been to a conference. I used this forum when I was applying to grad schools a few years ago, and I found it very helpful. More than anything it seems like there is very little information about what quantitative psychology is, and I had very little idea of what it was when I started considering entering this field. All I knew was that I liked math and psych, and this was a way of combining the two. Reading through GradCafe (especially reading responses from people who were in the field already) was very insightful, especially when they gave concrete examples of the types of projects that people worked with, the types of questions that they were trying to answer, the types of jobs that one could get after (in academia and industry), etc. I'll be happy to answer any questions that I can regarding the field and what we do. My answers are based on my experience only, and do not reflect on my program or my mentors.