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