Data is everywhere.
We generate new data with every social media post, digital transaction, and video of kittens.
This deluge of data has given rise to a new industry that is devoted to understanding the bits of information that may explain who we are and what we want.
While this type of data is mostly used to sell you more ‘stuff’; for scientists studying behavior, there is a tremendous capability to use this information for social good.
As a statistician with a background in both quantitative psychology (PhD) and biostatistics (MPH), I bring a unique perspective to my collaborations.
See my Bio/CV for more information.
Areas of Statistical Expertise
Longitudinal
Methods
Mixed Effects Regression
Latent Growth Curve Analysis
GEE/Marginal Models
Mixed Effects Hybrid Models
Cross-Lag Panel Regression
Autoregressive Latent Trajectory
Individual Fixed Effects Models
Joint Modeling
Quasi-Experimental Approaches
Instrumental Variables Approaches
Propensity Matching/Weighting
Interrupted Time Series
Marginal Structural Models
Difference-in-Difference
Event Study Approaches
See Statistical Resources for more info
Statistical/Machine
Learning
Growth Mixture Modeling
Latent Class/Profile Analysis
Recursive Partitioning
Hierarchical Clustering
Random Forest
Gradient Boosting
Substantive Research Areas
Child and Adolescent Behavioral Development: My work examines child and adolescent development as it pertains to the emergence of health behaviors. With specific focus on substance use and related mental health and behavioral outcomes, I explore these in observational research as well as in the context of school- and family- based interventions. Work in these areas has examined the impact of school-based health centers in improving grades and attendance, the role of school climate and other risk factors on substance use initiation, and the evaluation of how academic tracking can exacerbate disparities in minoritized groups.
Diabetes Prevention: I work on the evaluation of an employer based delivery of the CDC National Diabetes Prevention Program. This program of research examines the real-world effectiveness of these interventions as well as the cost-benefit of these programs to insurers. These evaluations are methodologically complex due to the self-selection that occurs among those who volunteer to participate, necessitating the use of various matching and propensity based techniques combined with quasi-experimental analytic approaches. I additionally work on a program for combating obesity in children through a family-focused diet and lifestyle intervention (RCT) as well as an administrative intervention for improving care access in diabetic retinopathy screening.
Health Services Research: My work in this area is multifaceted and examines the health care system at both a macro (e.g. governmental and insurance system policy) and micro level (e.g. hospital operations; medical education), with the goal of shifting policy at the local, state, and national levels. This work has examined changes to the health care delivery system via the Affordable Care Act, the role of insurer backed care coordination programs for improving patient outcomes, methodological approaches for segmenting high-cost/high-needs patient populations, and evaluations of scarce resource allocation policies (e.g. ICU beds and ventilators).
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Nicholas J Jackson, PhD MPH 