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An
Interesting Career in Psychology:
Statistical
and Methodological Consultant
Dale
N. Glaser,
PhD, Pacific
Science & Engineering Group
From
my first course in psychology as an undergraduate at the
University of California, Irvine, I became absolutely enamored
with this discipline. Even though I was relatively apprehensive
about taking the required one-year statistics course, the
professor (Robert Newcomb, who is still very active with the
Southern California Chapter of the American Statistical
Association) made the subject matter come alive. At that time, I
learned the importance of interweaving concept with algorithms:
it was not enough to just memorize, by rote, the various
equations without a conceptual and applied thread. Subsequently,
I went on to a masters program in counseling, with my primary
vocational aim to be a practitioner. I gained experience as a
vocational rehabilitation counselor, then proceeded to
management. As evident by my career trajectory, activities in
research and analysis (except instances of test evaluation and
interpretation) were generally subordinated to
counseling/personnel responsibilities.
With the aim of obtaining a PhD in psychology always a
consideration, I matriculated to a doctoral program in
industrial/organizational psychology. Again, my primary aim was
to be a practitioner in this domain, though I found, through an
internship at the Navy Personnel Research and Development Center
(NPRDC), that I not only had an aptitude for statistical
analysis (by way of SPSS-X on the mainframe), but that I also
enjoyed it. Though I gained employment as an organizational
development consultant, research and analysis became my true
passion. As circumstances would have it, I was asked to teach a
multivariate course in 1994 at United States International
University, and from then on I knew exactly what I wanted to do:
teach and conduct applied research. I worked in consumer
research and clinical research departments at a large health
care institution, entailing analysis of patient satisfaction
surveys as well as guiding the development of experimental and
non-experimental studies. Within this large health care network,
my expertise was being actively solicited, to the extent that I
was (not by design) serving as an internal consultant on many of
the studies being conducted across departments. Concurrently,
given the demand for adjunct faculty, I began instructing both
undergraduate and graduate statistics and research
design/psychometrics at San Diego State University, University
of San Diego, and Alliant International University/California
School of Professional Psychology.
With my ties to both the applied sector and academic arena, I
was making contacts with a wide array of sources, resulting in
various consulting opportunities. Though I wasn’t seeking them
out, I was referred to consult on a diverse array of projects.
What I found most appealing about statistical/methodological
consulting was that I wasn’t confined to one topical area. I
was consulting for health care institutions, marketing research
operations, educational programs, nonprofit organizations, etc.
Consulting afforded me the latitude to engage in a variety of
projects across varying disciplines. However, with this came the
reality that certain disciplines have an orientation in analysis
and methodology that may be unique to their domain. It became
incumbent that when consulting for a lung/heart/kidney
transplant center, I become sufficiently adept at survival
analysis. When engaged in a project testing the fit of a
longitudinal model with many data points across time, I needed
to have more than a passing familiarity with time series
analysis. Though a central interest of mine since my internship
at NPRDC, I needed to garner more sophisticated skills in
structural equation modeling (SEM). Even though my graduate
education served as a template for my statistical training, it
would not be an overestimate to claim that about 80% of my
current knowledge was obtained via self-instruction.
Based on my skills in multivariate and modeling techniques, I
was offered a senior statistician position at Pacific Science
& Engineering Group, a firm that specializes in applied,
experimental, and engineering psychology. Through this company,
I have been able to serve as a statistician/methodologist on
both internal and external projects. The projects have ranged
from fitting various complex quality of life models via SEM to a
study examining the group decision-making process in a
distributed environment to consulting on multiple health
care/nursing research studies for both academic and health care
institutions. Since then, I have also been asked to serve as an
ad hoc reviewer for various journals (e.g., Psychological
Methods) and on editorial boards (e.g., Structural
Equation Modeling). Despite my orientation as an applied
researcher, my consulting has also culminated in publications in
such diverse journals as Human Performance, Heart and
Lung, and American Journal of Critical Care.
Even though many of us are not trained as mathematical
statisticians, it is my contention that our grounding in
methodology, design, and interpersonal communication confers
upon those with a quantitative orientation in the psychological
sciences to serve aptly as methodologists/statisticians.
Admittedly, many of the articles in the statistical literature
(e.g., Journal of American Statistical Association, Biometrics,
Statistics in Medicine, etc.) may appear arcane; however,
the bulk of my consulting has not involved the complexities of
mathematical modeling that might be beyond my scope. Rather,
much of my work has involved domains that, as a psychological
scientist, I am well equipped to consult on (e.g.,
psychometrics). However, there are occasions when a project
dictates an analytical strategy that may be entirely novel. An
example of such an undertaking was when I needed to learn the
intricacies of spectral analysis for an electromyogram (EMG)/workload
study. Though those in health psychology may be versed in this
technique, it was a new one for me!
Some global recommendations for those interested in
statistics: (1) Become involved in the American Statistical
Association (ASA), including your local chapter. (2) Remember,
you may be competing against those specifically trained in the
discipline you are interested in exploring (e.g.,
biostatisticians, econometricians, etc.), so it will serve you
well to absorb the language unique to that particular
environment. (3) A random perusal of the applied statistician
positions in AMSTAT News (monthly publication of the ASA)
finds that virtually all the large manufacturing/pharmaceutical
concerns require SAS programming experience. Thus, the more
software you can learn (besides SPSS), the more marketable you
will become. I have been absolutely thrilled with my career
trajectory. For me, the merging of applied research with
academia has fulfilled a life-long ambition! •
(Originally published in the
November/December 2001 issue of Psychological
Science Agenda, the newsletter of the APA Science Directorate.)
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Interesting
Careers in Psychology....
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