"The most satisfactory arrangement occurs when the person who understands the scientific issues and the person with the statistical expertise is the same person" - Anonymous*
I have a concentration in statistics as part of my PhD, as well as an MPH in biostatistics. I have focused most of my training on the analysis of complex, longitudinal, observational data. I am the statistical consulting editor for International Journal of Behavioral Medicine, consult with colleagues at UK on data analysis questions, and have had data analysis roles on funded research projects (including my own.) Selected training and analyses are detailed below.
Multilevel Modeling and Longitudinal Data Analysis
APA Advanced Training Institute: Longitudinal Methods, Measurement, and Models
University of Illinois, Champaign-Urbana: EDPS/PSYCH/STAT 587 Multilevel Models
University of Kentucky: BST 762 Longitudinal Data Analysis
University of Kentucky: BST 761 Time to Event Analysis
Multivariate Analysis
UCLA: PSYCH 253 Factor Analysis
University of Kentucky: STA 677 Applied Multivariate Analysis
Software
University of Kentucky: CPH 535 Databases and SAS Programming
University of Kentucky: STA 651 Advanced Programming in R
StatCamp: SEM in MPlus
StatCamp: Meta-Analysis in R
StatCamp: R for Data Science
Analysis examples
Multilevel, Longitudinal Models
Segerstrom, S.C. (2014). Affect and self-rated health: A dynamic approach with older adults. Health Psychology, 33, 720-728. (Longitudinal MLM in PROC MIXED.)
Segerstrom, S.C., Eisenlohr-Moul, T.A., Evans, D.R., & Ram, N. (2015). Repetitive thought dimensions, psychological well-being and perceived growth in older adults: A multilevel, prospective study. Anxiety, Stress, and Coping, 28, 287-302. (Multivariate, longitudinal MLM in PROC MIXED.)
Segerstrom, S.C., Geiger, P.J., Combs, H.L., & Boggero, I.A. (2016). Time perspective and social preference in older and younger adults: Effects of self-regulatory fatigue. Psychology and Aging, 31, 594-604. (MLM as applied to experimental data in PROC MIXED.)
Segerstrom, S.C., Kasarskis, E., Fardo, D., & Westgate, P.G. (2018). Socioemotional resources and well-being in amyotrophic lateral sclerosis patients and caregivers: A longitudinal, dyadic analysis. (Longitudinal, dyadic MLM in PROC MIXED.)
Multivariate Analysis
Segerstrom, S.C., Stanton, A.L., Alden, L.E., & Shortridge, B.E. (2003). A multidimensional structure for repetitive thought: What’s on your mind, and how, and how much? Journal of Personality and Social Psychology, 85, 909-921. (Factor analysis, MDS)
Segerstrom, S.C., Roach, A.R., Evans, D.R., Schipper, L.J., & Darville, A.K. (2010). The structure and health correlates of trait repetitive thought in older adults. Psychology and Aging, 25, 505-515. (MDS)
Measurement and Methodology
Segerstrom, S.C., & Smith, G.T. (2012). Methods, variance, and error in psychoneuroimmunology research: The good, the bad, and the ugly. In S.C. Segerstrom (Ed.), Oxford Handbook of Psychoneuroimmunology (pp. 421-432). New York: Oxford.
Out, D., Granger, D.A., Sephton, S.E., & Segerstrom, S.C. (2013). Disentangling sources of individual differences in diurnal salivary a-amylase: Reliability, stability, and sensitivity to context. Psychoneuroendocrinology, 38, 367-375. (Generalizability analysis.)
Segerstrom, S.C., Boggero, I.A., Smith, G.T., & Sephton, S.E. (2014). Variability and reliability of diurnal cortisol in younger and older adults: Implications for design decisions. Psychoneuroendocrinology, 49, 299-309. (Generalizability analysis.)
Segerstrom, S.C., Combs, H.L., Winning, A., Boehm, J.K., & Kubzansky, L.D. (2016). The happy survivor? Effects of differential mortality on life satisfaction in older age. Psychology and Aging, 31, 340-345. (Statistical approaches to missing data.)
Segerstrom, S.C., Sephton, S.E., & Westgate, P.G. (2017). Intraindividual variability in cortisol: Approaches, illustrations, and recommendations. Psychoneuroendocrinology, 78, 114-124. (Statistical approaches to intraindividual variability.)
Segerstrom, S.C. (2019). Between the error bars: How modern theory, design, and methodology enrich the personality-health tradition. Psychosomatic Medicine, 81, 408-414. (Methodology and statistical approaches to variability in individual difference measures, including biomarkers.)
* From a faculty candidate's letter of recommendation.