What area of Quant Psych most lucrative / best prospects for PhDs?

#1
Hi,

If you're interested in a Quant Psych PhD, but you're not particular about what area you study within it, what specific Quant Psych areas would make you most employable outside of academia?

So for example, is there a certain kind of analysis (e.g., multilevel modeling) that is currently in very high demand in industry/government?

Or is there a certain area of application (eg, genomics) that is currently in very high demand in industry/government?



As examples here are some of the "research interest clusters" that I've seen on various Quant Psych PhD program's faculty pages or research pages:



From USC:

Robust Statistical Inferences. Research on robust inferences strives to understand the most reliable statistical features of any behavior. This work includes a complete revision of univariate and multivariate statistics from the direct identification of outliers and influential observations. This topical area is led by Rand Wilcox.
Psychometrics and Measurement. The basic principles of psychological measurement are used and applied to scale development in several content areas. This includes the uses of recent advances in Item Response Theory (IRT) and in Common Factor Analysis (CFA) are applied to scale development, and form the basis of computer adaptive testing (CATI). This topical area is led by John McArdle.
Behavior and Molecular Genetics. Individual differences in psychological behaviors are a complex function of both genetic and non-genetic sources, and advances in statistical analysis have played a crucial role in new results. We examine the basic benefits and limitations of family data, including twins, and these issues are combined with the use of measured genotypes to better understand these sources of variation. This topical area is led by Laura Baker and Carol Prescott.
Decision Making in Real Life. Individuals and groups make many important real-life decisions about health and work, marriage and family planning, and about engaging in risky behaviors. We study the elementary processes behind such decisions, including the development of group and individual utility functions. This topical area is led by Richard John.
Longitudinal Dynamic Changes. The accurate measurement of developmental changes from longitudinal data are a mainstay of developmental, personality, and motivational psychology. Recent advances in latent trajectory analysis, multi-level survival analysis, growth mixture modeling, and systems dynamics modeling, are all combined with contemporary psychometric measurement models. This topical area is led by John McArdle.



From Fordam University:

With help and guidance from faculty mentors, our doctoral students perform research in one of the following areas:
  • Models of decision and choice
  • Bayesian statistics
  • Structural equation modeling
  • Item response theory
  • Hierarchical linear modeling
  • Longitudinal data analysis
  • Propensity score analysis
  • Missing data analysis
  • Categorical data analysis
  • Correspondence analysis
  • Scaling methods
  • Profile analysis


From MSU:

Research Specializations
Doctoral students in the MQM program select between two specializations: Measurement, or Quantitative Methods.

Students interested in issues relating to large-scale assessment, instrument development and survey administration adopt the Measurement specialty.

Students interested in the development, extension or modification of statistical methods or the rigorous application of sophisticated statistical or econometric methods to examine empirical issues related to educational research adopt the Quantitative Methods specialty. Students in the Quantitative Methods specialty are also trained in the quantitative basis for causal inference and educational evaluation that informs policy.




From University of Minnesota:

Quantitative/Psychometric Methods (QPM): Our Quantitative/Psychometric Methods area utilizes multivariate methodology such as
* factor analysis
* structural equation modeling
* item response theory
* computerized adaptive testing
* multi-way data analysis
* nonparametric methods.

Our faculty and students conduct research in
* applied statistics
* experimental design
* correlational methods
* advanced test theory
* psychological scaling
 

spunky

Doesn't actually exist
#2
most employable outside of academia?
Honestly (and as someone who specifically works in this area), if your ultimate goal is to work outside of academia you should probably bypass Quantitative Psychology altogether and opt for a degree in Statistics, Biostatistics or Machine Learning/Data Science, which is a very hot topic today.

Keep in mind that, for most employers who are not academics or related to the field, the word that catches their att'n is going to be *Psychology* and not Quantitative. They're probably going to think you are more related to Clinical Psychology than Statistics, which already places you at a disadvantage to other potential candidates that come from a Statistics/BioStats/Data Science background.

Now, if you're still really interested in psychology and methodology in the social sciences, the sub-area of expertise that would probably land you a job outside academia would be Psychometrics. More specifically, anything to do with Item Response Theory, Computerized Adaptive Testing, etc. Educational testing is very big in the U.S. and big testing companies like Pearson or ETS are always hiring people.
 

hlsmith

Omega Contributor
#3
It dependents on what type of job.

I would think mult-level modeling and longitudinal analysis can be used in almost any sector. I can't directly see employers going after some of the others even though they may be applicable to the field.

P.S., you may not even need a doctorate if you are thinking non-academia. People can master and excel in these areas without formal education and a terminal degree.
 
#4
Thanks for the advice, both of you!

Spunky - I’m not dead set on quant psychology, but I’d like as many options as possible. My background is all psych, so that’s where I’d be most likely to land an academic job. But the academic job market being what it is, I am definitely not comfortable investing 5-6 years in a doctorate that leaves me only employable in academia! I have definitely gotten the sense that biostatistics is more of a growth industry than any of the explicitly quant psych fields (eg standardized testing). But at the same time a biostats PhD would severely limit my academic prospects in psychology.

If there’s one area of quant psych I’m interested in above others, it’s the specialty that I guess you could call “social science statistics reform.” The kind of stuff done by guys like Rex Kline, Rand Wilcox, & Geoff Cumming. Meta-analysis is also super interesting. Basically, anything with broad application that feels like you’re pushing forward the whole field of psychology as a science. However, I feel like that stuff is probably the MOST academically-oriented kind of quant psych one could possibly do, so it would probably limit my non-academic options the most, wouldn’t you think?
 
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spunky

Doesn't actually exist
#5
Spunky - I’m not dead set on quant psychology, but I’d like as many options as possible. My background is all psych, so that’s where I’d be most likely to land an academic job. But the academic job market being what it is, I am definitely not comfortable investing 5-6 years in a doctorate that leaves me only employable in academia! I have definitely gotten the sense that biostatistics is more of a growth industry than any of the explicitly quant psych fields (eg standardized testing). But at the same time a biostats PhD would severely limit my academic prospects in psychology.
Well, this is an interesting choice that you have before you then. On the one hand, I do agree with you. The computer coding and data-analytic skills that you’d learn on a Quant Psych program are probably going to give you more opportunities for positions outside academia. HOWEVER (and contrary to common sense), being fully focused on Quant Psych tends to work against you when it comes to applying for a professor position. Leona Aiken (who has done A LOT of very interesting research as far as this profession goes, the training in Statistics and Methodology at the graduate level in Psychology, etc.) has a very interesting (and somewhat disheartening) video on this topic. Most university programs pay lip service to the idea of training and teaching Quantitative Psychology but aren’t really interested in hiring Quant Psych people. They’d rather go for substantive/applied people (Social, Personality, I/O, etc.) that maybe have a sub-expertise in quantitative methods, if at all. She calls these people “twofers”.

As a side note on this, you don’t *have* to become a Quantitative Psychology just to obtain the training that you need. We have our very own success story here, Jake, who started out as a Social Psychologist but has now fully transitioned into analytics. At the end of the day it comes down
to making sure you don’t drop the ball when it comes to your quantitative training, coding and data analysis skills.




If there’s one area of quant psych I’m interested in above others, it’s the specialty that I guess you could call “social science statistics reform.” The kind of stuff done by guys like Rex Kline, Rand Wilcox, & Geoff Cumming. Meta-analysis is also super interesting. Basically, anything with broad application that feels like you’re pushing forward the whole field of psychology as a science. However, I feel like that stuff is probably the MOST academically-oriented kind of quant psych one could possibly do, so it would probably limit my non-academic options the most, wouldn’t you think?
You’re right, this would be an incredibly academic-oriented research programme. I honestly can’t see how you could market this into industry and, if I may paraphrase your own words, it would probably “severely limit your industry prospects”. Keep in mind that, until you prove you’re capable of doing the necessary programming/quantitative analysis, you’re still at a disadvantage from people who come from backgrounds in Computer Science, Engineering, Statistics, etc. If you would like to consider an industry career as an option, it would be to your advantage to consider a research programme that tackles problems industry-type people care about. That’s why I suggested Psychometrics as a first option because that’s a skill that can be very easily tailored to gov’t and private industry positions devoted to educational testing. Areas related to the analysis of fMRI data (which is now very popular in Bio/NeuroPsych) would also probably open up doors in the fields of health and medicine. But yeah, these “meta” topics concerned with Reproducibility/Replicability, the practice of science in Psychology, etc… super academic. Not what you’d think of if you wanna keep a sensible “Plan B” to work outside a university.

My personal 2 cents (so take it with a grain of salt). Now that I’ve been interviewing for academic positions I decided very quickly this is not for me. There are all these outside aspects and evaluation criteria like how many grants are you getting, how much are you publishing per year, what are the impact factor of those journals, what’s your h-index of citations, etc. that I can’t help but realize proper, solid research is often a very, very VERY low priority when it comes to what people think is important before you get tenure. And not only that, the sacrifices that people make to get a good position (at least here in North America) are, in my mind, not what I would envision myself doing for a decade before I can get tenure. I come from an entrepreneurial background and co-own a business with my husband. So I use my business to pay the bills and my post-doctoral appointment to keep me “on the loop”, so to speak, of what’s going on in research and academia. But I honestly feel the neo-liberal model that we have going on in universities and the commoditization of education has created an environment where I’d need to make more personal and professional sacrifices than what I’d be willing to do for any other, 9-to-5 job. That’s why, although I DO NOT agree with it, I totally understand people who p-hack or HARK their way into a job in academia. Like my grandma (who lived through periods of national food rationing) used to say, “you wouldn’t believe what people are capable of if you mess with their food”.
 
#7
One more question (for Spunky or anyone else) - do you think that someone who got a PhD in Quant Psych would be competitive for the same kind of jobs as people who have a PhD in Education Evaluation, Measurement & Statistics focus?

Would it depend on your dissertation topic, or would any Quant Psych grad be able to spin themselves as fairly competitive for those kinds of quantitative education jobs?

I would imagine that for education jobs, you'd want a background in psychometrics, MLM, factor analysis, SEM, and perhaps longitudinal analysis, but I also imagine that a Quant Psych person would get plenty of that in coursework (regardless of dissertation topic).
 

spunky

Doesn't actually exist
#8
One more question (for Spunky or anyone else) - do you think that someone who got a PhD in Quant Psych would be competitive for the same kind of jobs as people who have a PhD in Education Evaluation, Measurement & Statistics focus?

Would it depend on your dissertation topic, or would any Quant Psych grad be able to spin themselves as fairly competitive for those kinds of quantitative education jobs?

I would imagine that for education jobs, you'd want a background in psychometrics, MLM, factor analysis, SEM, and perhaps longitudinal analysis, but I also imagine that a Quant Psych person would get plenty of that in coursework (regardless of dissertation topic).
To be honest, both areas are pretty much identical and, depending on the program, even the coursework is the same. I come from an Educational Measurement background (that's what officially says in my PhD), but I both have an appointment in the Quantitative Methods program in the Psychology department and have TA'd, taught and taken courses with them. If you compare each program side by side the only difference tends to be that Educational Measurement people take courses in Item Response Theory and most Psych people don't (it's usually a matter of sample size issues. IRT is a large N technique and most psych experiments don't meet the criteria). Nevertheless, that doesn't mean you can't specialize in that. So far I know 2 people with a Quant Psych background who are teaching in Educational Measurement program and one who did his PhD in an Ed Measurement program teaching in a Psych Dept.

As you mentioned, it usually comes down to the focus. Like if you do more research/publish stuff in psychometrics and measurement issues, you can easily jump ship between programs.