BSSM Research Methods and Data Core

    The BSSM Data Core is a resource to help members of our department identify needed experts for collaboration and/or consultation on data management, analyses and study methods. Data expertise and interests of BSSM faculty and staff members are listed below. You may contact team members directly by their listed email.

    Team Members

    • Email:  ag04f@fsu.edu
    • Software:Stata, Mplus, Excel, Qualtrics, NVivo, ATLAS.ti
    • Study Type: Cross-sectional studies, Measurement development, Qualitative studies
    • Unfavorite Study Type: Cohort studies / longitudinal studies
    • Study Component:  Research idea initiating and/or research question/hypothesis generating, Data collecting, Data cleaning, Data analyses
    • Unfavorite Study Component:  Questionnaire or other measurement designing, Data collecting
    • Analysis Method:  Basic descriptive statistical analyses, t-test, Chi-squared test, Correlation, Multiple linear regression, Logistic regression, Structural equation modeling, Inter-rater reliability
    • Interested Population: Pediatric population Minorities
    • Interested Topic:P reventive dental procedures.
    • Collaboration Availability: No limitation, always interested or available
    • Time Availability: F or both collaboration and detailed actual work
    • Self-Description: Affan Ghaffari, PhD is a specialized research faculty currently working on projects associated with substance abuse policy (CDC-funded Overdose Data to Action) and provision of family planning services (Florida Family Planning Services) at FSUCOM. For all these projects, he has been involved in survey instrument development, quantitative data analysis, conducting qualitative interviews, and performing qualitative data analysis.

      He was previously at Columbia University School of Nursing involved in research relating to nurse practitioner (NP) organizational climate and workforce outcomes along with the validation of existing survey instruments relating to NP organizational climate and errors of care omission within primary care.The survey tools he worked with include the Nurse Practitioner Primary Care Organizational Climate Questionnaire (NP-PCOCQ) and the Errors of Care Omission Survey (ECOS).His doctoral training took place at Texas A&M School of Public Health and his dissertation involved application of the Relational Coordination instrument in different healthcare contexts.

      He has a broad background in health services research, with specific training and expertise in instrument development, survey data analysis, qualitative methodology, and qualitative data analysis.
    • Email:  jeffrey.harman@med.fsu.edu
    • Software: SAS, Stata
    • Study Type: Cross-sectional studies, Cost analysis, Medicaid/Medicare/Healthcare claims data analysis
    • Unfavorite Study Type: Case-control studies, Cohort studies / longitudinal studies, Clinical trials / interventional studies
    • Study Component: Research idea initiating and/or research question/hypothesis generating, Data cleaning, Data integrating (combining & merging), Data analyses
    • Unfavorite Study Component: Questionnaire or other measurement designing, Data collecting
    • Analysis Method: Basic descriptive statistical analyses, t-test, Chi-squared test, Correlation, ANOVA, Multiple linear regression, Logistic regression, Poisson regression, Multilevel models/Mixed models
    • Interested Population: Underserved
    • Interested Topic:Health services research, health policy analysis, program evaluation
    • Collaboration Availability: No limitation, always interested or available
    • Time Availability:For consultation only but no/less time for detailed actualwork
    • Self-Description: My training focused on statistics and econometrics, particularly on statistical methods observational research
    • Email: jon.mills@med.fsu.edu
    • Software: S AS, Stata, Excel
    • Study Type: Cross-sectional studies, Case-control studies, Cohort studies / longitudinal studies, Cost analysis, Medicaid/Medicare/Healthcare claims data analysis
    • Study Component: Research idea initiating and/or research question/hypothesis generating, Data cleaning, Data integrating (combining & merging), Data analyses, Other
    • Unfavorite Study Component: Research idea initiating and/or research question/hypothesis generating
    • Analysis Method: Basic descriptive statistical analyses, t-test, Chi-squared test, Correlation, ANOVA, Multiple linear regression, Logistic regression, Poisson regression, Marginal structural models
    • Interested Population: People with HIV, Medicaid
    • Interested Topic: Large epidemiological observational studies - treatment effectiveness estimation with observational data
    • Collaboration Availability: Co-authorship, Research topic
    • Time Availability: For consultation only but no/less time for detailed actualwork
    • Self-Description: Area of Expertise: HIV and mental health, HIV and trauma, causal inference with observational data, "Big Data"
    • Email:  katelyn.graves@med.fsu.edu
    • Software: SAS, Stata, Mplus, Excel, Qualtrics
    • Study Type: Cross-sectional studies, Cohort studies / longitudinal studies, Medicaid/Medicare/Healthcare claims data analysis
    • Study Component: Questionnaire or other measurement designing, Data cleaning, Data integrating (combining & merging), Data analyses
    • Unfavorite Study Component: Research idea initiating and/or research question/hypothesis generating, Power analysis (Sample size calculating), Data collecting
    • Analysis Method: Basic descriptive statistical analyses, t-test, Chi-squared test, Multiple linear regression, Logistic regression, Poisson regression, Multilevel models/Mixed models, Structural equation modeling
    • Interested Population: I'm pretty flexible, but have done the most work looking at older adult populations, socioeconomically disadvantaged groups, and also individuals with substance use disorder.
    • Interested Topic: My degree is in sociology with a focus on demography/population dynamics, but have been working on all sorts of public health/population health topics since starting at COM. I really enjoy assisting with research methods, so am flexible with the topics.
    • Collaboration Availability: Funding, Co-authorship, Research topic, Other (Generally interested if my schedule allows)
    • Time Availability: For consultation only but no/less time for detailed actualwork
    • Self-Description: I have a background in demography and sociology, with an emphasis on biosocial health. I have a wide variety of research interests, though I tend to prefer helping others with the methods for their research projects rather than focus on any one specific area of interest. I have experience with a broad range of demographic and statistical analyses, utilizing software programs such as Stata and SAS. I also have experience managing and analyzing Medicare and Medicaid claims data. I am involved in several program evaluations aimed at assessing public health programs, including the Overdose Data 2 Action program, and Florida Medicaid Family Planning Waiver Program.
    • Email:m artina.luchetti@med.fsu.edu
    • Software: SPSS, Mplus, Excel, GPower, Redcap, Qualtrics, Other  (R: only for adjusting existing syntaxes)
    • Study Type: Cross-sectional studies, Case-control studies, Cohort studies / longitudinal studies
    • Unfavorite Study Type: Cross-sectional studies
    • Study Component: Research idea initiating and/or research question/hypothesis generating, Questionnaire or other measurement designing, Data collecting, Data analyses
    • Unfavorite Study Component: Data cleaning, Data integrating (combining & merging)
    • Analysis Method: Basic descriptive statistical analyses, t-test, Chi-squared test, Correlation, ANOVA, ANCOVA, Multiple linear regression, Logistic regression, Multilevel models/Mixed models, Structural equation modeling, Meta-analysis, Other (Analytic approaches to address intensive longitudinal assessment (ecological momentary assessments))
    • Interested Population:Aging adults 40+, caregivers, patients from memory clinics (reporting subjective complaints or cognitive impairment)
    • Interested Topic:Personality, loneliness, cognitive/memory function, classification of cognitive status, dementia, some biomarkers (e.g., CRP), health behaviors, smartphone-based assessments of cognition, feelings and behaviors
    • Collaboration Availability: Research topic
    • Time Availability: Other (For collaboration and actual work depending on the research topic)
    • Self-Description: In my past work, I have applied longitudinal methodologies to identify psychological factors (e.g., personality) that contribute to memory and cognitive health across the adult lifespan. In recent years, I specifically directed attention to socio-relational factors, particularly loneliness, that affect risk of late-life cognitive impairment and dementia (Luchetti et al., 2020, Int J Geriatr Psychiatry; Sutin et al., 2023, Int Psychogeriatr) and focused on relational dynamics, within spouses (Luchetti et al. 2022, J Gerontol B Psychol Sci) and caregivers (Luchetti et al., 2021, Aging Mental Health). My expertise pertains aging and cognition, and use of ambulatory assessments is fundamental to the project. II have experience in the use of large and complex datasets (e.g., Health and Retirement Study and other public aging cohorts), and application of advanced statistical models in Mplus(e.g., latent change models). 

      Since 2015, I work as a Faculty at the Florida State University in close collaboration with co-investigators, Drs. Sutin and Terracciano.
    • Email:  yuxia.wang@med.fsu.edu
    • Software: SAS, SPSS, Excel, GPower, Quickbase, Redcap, Qualtrics, Chatgpt, Other  (For R and Stata, I can provide some consultation if needed, but not for programming since I did not use them for a while)
    • Study Type: Cross-sectional studies, Case-control studies, Cohort studies / longitudinal studies, Clinical trials / interventional studies, Measurement development
    • Unfavorite Study Type: Medicaid/Medicare/Healthcare claims data analysis, Qualitative studies
    • Study Component: Research idea initiating and/or research question/hypothesis generating, Questionnaire or other measurement designing, Power analysis (Sample size calculating), Data collecting, Data cleaning, Data integrating (combining & merging), Data analyses
    • Unfavorite Study Component: Power analysis (Sample size calculating)
    • Analysis Method: Basic descriptive statistical analyses, t-test, Chi-squared test, Correlation, ANOVA, ANCOVA, Multiple linear regression, Logistic regression, Poisson regression, Multilevel models/Mixed models, Structural equation modeling, Inter-rater reliability, Meta-analysis
    • Interested Population: Wide range without limit
    • Interested Topic: Wide range without limit
    • Collaboration Availability: No limitation, always interested or available
    • Time Availability: For both consultation and detailed actualwork
    • Self-Description: As a biostatistician, researchers' interest is my interest, no limit on population and research topics. The subjects involved in the past mostly were human, but also had animals and objects. 

      I work with researchers from the beginning stage of a study and follow the whole process, like questionnaire design, data collection, data cleaning & management, data analyses, and paper publishing. I enjoy each component of my work. 
    • Email:  yang.hou@med.fsu.edu
    • Software: SPSS, R, Mplus, Excel, Redcap
    • Study Type: Cross-sectional studies, Cohort studies / longitudinal studies, Clinical trials / interventional studies, Measurement development
    • Study Component: Research idea initiating and/or research question/hypothesis generating, Questionnaire or other measurement designing, Power analysis (Sample size calculating), Data collecting, Data cleaning, Data integrating (combining & merging), Data analyses
    • Analysis Method: Basic descriptive statistical analyses, t-test, Chi-squared test, Correlation, ANOVA, ANCOVA, Multiple linear regression, Logistic regression, Multilevel models/Mixed models, Structural equation modeling, Inter-rater reliability, Meta-analysis
    • Interested Population: Individuals with rare diseases; adolescents in general
    • Interested Topic: Neurobehavioral (cognitive, academic, socioemotional, behavioral) development of individuals in underrepresented groups.
    • Collaboration Availability: Funding, Co-authorship, Research topic
    • Time Availability: For both consultation and detailed actualwork
    • Self-Description: Dr. Yang Hou is an assistant professor in the Department of Behavioral Sciences and Social Medicine and Director of the Development, Equity, and Resilience (DEaR) Lab at the College of Medicine at Florida State University. She received a Ph.D. in Human Development and Family Sciences at the University of Texas at Austin. Her research program aims to inform the development of evidence-based intervention programs personalized to marginalized groups to promote their mental health and to advocate patient-centered care through two primary goals: 1) To understand how biopsychosocial factors influence the neurobehavioral (cognitive, academic, socioemotional, behavioral) development in underrepresented groups; 2) To promote clinical and developmental science with advanced quantitative methods. Her current primary line of research aims to use innovative and advanced quantitative methods to provide a more comprehensive understanding of the patterns and predictors of neurobehavioral development of individuals with NF across the lifespan. She is enthusiastic about stimulating collaborative efforts and open science practice to accelerate intellectual discovery in the NF field. She has expertise in various statistical approaches, such as multilevel modeling, time-varying effect modeling, structural equation modeling, and latent profile analysis. 

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