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Mind Alchemy
Mind Alchemy
Precision Psychometrics for Marketing & Evaluation

Meet Dr. Michelle Raab

Headshot for Dr. Michelle Lopez Raab, behavioral scientist and psychometrician

Psychometrician. Marketer. Storyteller.


If you meet Dr. Michelle Raab, she will seem unassuming. Beneath the surface though, there are layers of knowledge and experience that have been integrated and transmuted into a potent catalyst that turns data into intelligence and intelligence into actionable plans.


Learning how to write a press release on a manual typewriter is one element that is transfused with her insatiable appetite for sketching the world through numbers and equations.


Isaac Asimov’s Foundation series with its psychohistory not only captured her imagination where human behavior could be predicted through mathematical calculations, but it was blended into her mindscape of seeing the world that could be described with fanciful numerical notations, which led her to taming the mythical beast known as the Algorithm found in so many parts of our commercial world from SEO to listings on commercial seller’s platforms.

Melding Quantitative Research With Marketing & Storytelling

Being able to teleport between the quantitative universe and the storyverse, Dr. Raab can weave a tale from the outlines and sketches of demographic statistics that stirs the heart and engages the mind.  She has done this in political settings, carefully and strategically placing smoke and mirrors to project a narrative that would help the grassroots organizations that she was creating messaging for.


Dr. Raab dives down into the catacombs of data to find nuggets of information that are hidden on the surface. Finding subgroups or segments within a data set is like finding gold in a mining cave for her. Unlike many data analysts, she understands the unique peculiaritiesof data research when it is derived from people. Years of training and experience as a data research consultant have honed her skills in the collection, management, analysis, and interpretation of people data.


Dr. Michelle Raab’s unique skill set is usually found only in academia, psychological assessment corporations, or large cap corporations. She doesn’t like being usual. She prefers to forge her own path. As a versatile consultant in market research and behavioral science, located near Pittsburgh, PA, she offers a distinctive blend of expertise in data analysis and storytelling.

There is more than one way to climb the mountain, because you have the whole mountain to choose from.


Research Experience & Certifications

​Dr. Raab is a dedicated professional with a robust academic background spanning psychology, clinical studies, and quantitative methods.


Dr. Raab earned her PhD in experimental psychopathology, with a subspecialty of quantitative methods from the University of Hawaii at Manoa. Prior to that, she completed a Master of Arts in psychology, specializing in clinical studies at the same institution. Her expertise also lies in psychometrics, a foundational aspect of our market research methodology. Earlier in her academic journey, Dr. Raab achieved a Master of Arts in Marriage and Family Therapy from Argosy University, Honolulu Campus. Her academic journey initially began at Trinity University in San Antonio, Texas where she received a Bachelor of Arts in English, with a minor in Business Administration.


Dr. Raab brings a wealth of experience as a behavioral science and data manager from her tenure at one of the United States' foremost research institutions, the National Center for PTSD. She has also been an instructor at the University of Hawaii, Manoa Campus.

Dissertation

Dr. Raab’s dissertation for her PhD in experimental psychopathology from University of Hawaii, Manoa was titled, “Improving Our Classification System for the Treatment of Individuals Who Have Experienced Traumatic Events: The Contribution of Unsupervised Statistical Learning to Our Existing Methods.” Click here to read it.

Abstract:

Rationally derived theories have had a limiting effect on the advancement of psychology as a science, compared to theories born out of or tested by empirical studies. As an example, while the diagnostic system (DSM) has been informed by science, the categories have not often been empirically derived (DSM-I, 1953; DSM-II, 1968; DSM-III, 1980, DSM-IV-TR, 2000; DSM-5, 2013). There is an emerging inclusion of empirical methods in the diagnostic classification system, as seen with some diagnostic categories of the DSM-5 (2013; Krueger, Derringer, Markon, Watson, & Skodol, 2012); however, there are many criteria and categories that have gone untested (Kramer et al., 2016). And, simply using hypothesis testing may not be sufficient in generating new knowledge. To improve our methods, we add to our current research and statistical methods through the use of unsupervised statistical learning, where data are allowed to tell their own story. Two statistical learning techniques, k-means cluster analysis and finite mixture modeling (Duda, Hart, & Stork, 2012; Hastie et al., 2009; James, Witten, Hastie, & Tibshirani, 2013) were applied to a data set collected on university students who had been displaced in the aftermath of Hurricane Katrina to understand the relationship between resource loss and stress. These techniques were used to demonstrate how to explore the data so that unanticipated knowledge could be distilled from the data. Findings showed that this data set was not easily studied using k-means cluster analysis, because the structure of the multivariate data did not contain clearly defined subgroups. Exploring the data using finite mixture modeling did, however, yielded possible areas of further research, such as the relationship of gains and losses to items on the depressive scale. However, conclusions about the relative performance of these techniques should not be made without the use of simulated data. This research study demonstrated the importance of expanding our techniques to explore what the data can tell us, as the findings would not have been revealed had the data only been explored by using hypothesis testing. Future research should include unsupervised statistical learning as a method to advance knowledge and classification in psychological research.

Professional Affiliations

American Psychological Association logo

American Psychological Association

2006 to Present
American Statistical Association logo

American Statistical Association

2013 to Present

American Marketing Association logo

American Marketing Association

2023 to Present

Schedule a Meeting with Dr. Raab

Want to know more about this Pittsburgh-based award winning behavioral scientist? Get in contact with us! You can also find Dr. Raab on LinkedIn where she regularly posts about psychology, quantitative research, psychometrics, and more. Read our client reviews on Google and DesignRush.

Privacy Disclaimer

As a professional consultant, Dr. Michelle Raab places the utmost importance on client confidentiality, ensuring that all information shared remains strictly confidential and is handled with the utmost discretion.

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