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Johns Hopkins Alzheimer's Disease Resource Center for Minority Aging Research


The overall mission of the Analysis Core is to empower the AD-RCMAR with the analytic and data management support and strong statistical expertise that are needed to advance research on ADRD, minority aging, and health disparities.


The Core is co-led by Qian-Li Xue, PhD, associate professor in the Johns Hopkins Department of Medicine Division of Geriatric Medicine and Gerontology, and Jeannie-Marie Leoutsakos, PhD, associate professor in the Department of Psychiatry and Behavioral Sciences Division of Geriatric Psychiatry and Neuropsychiatry. Xue and Leoutsakos bring complementary methodological expertise to the Core evidenced by: Xue’s statistical expertise in the analysis of longitudinal data, missing data and multivariate outcomes and substantive research in the realm of cognitive function, frailty, and disability, and Leoutsakos’ expertise with scale development and refinement and 20-year track record of Alzheimer disease-related research and publishing. In addition to quantitative expertise, Marcela Blinka, PhD, has recently joined our team to be the expert on qualitative research methods. Blinka is a highly experienced social worker and researcher with substantial expertise in community work and the role that communication plays in designing community research projects with minority populations.


  1. Biostatistical expertise with a strong history of collaborating in gerontological research and education.
  1. A remarkable potential data resource, consisting of the multiple population- and intervention-based studies led by researchers at Johns Hopkins University, including assessments on more than 27,000 older adults, and, if aggregated, could provide new ability to evaluate individual, societal, and environmental causes of cognitive decline and functional loss in late life.

Analysis Core Aims

Under the direction of the Administrative Core (AC), and in close collaboration with the Research Education Component (REC) and the Community-Liaison and Recruitment Core (CLRC), the Analysis Core aims to contribute to the goals of the AD-RCMAR by:

     (1) Working with REC to:

  1. Provide methodological expertise in support of the conceptualization, design, implementation, analysis, and interpretation of research conducted by the RCMAR Scientists;
  2. Provide access to modern data acquisition and management tools and emerging computing technologies;
  3. Provide mentoring to junior faculty supported by REC, with the goal of maximizing their skills in study design, data analysis, effective collaboration with biostatistical colleagues, and ability to translate research findings into clinical and community-based interventions and practice.

     (2) Collaborating with AC to:

  1. Provide scientific leadership for the AD-RCMAR and heighten visibility of our research by building and maintaining an AD-RCMAR website;
  2. Disseminate measures, methods, and findings to the national RCMAR and AD-RCMAR networks and affiliated investigators.

     (3) Partnering with CLRC to study recruitment and retention of minority older adults.

Through these activities, we hope to promote and facilitate the proactive organization of biostatistical support needed to address methodologic challenges in the study of etiology, pathogenesis, and consequences of Alzheimer's disease and aging in minority older adults.


Our Core aims to strengthen REC support of promising junior investigators from underrepresented backgrounds by maximizing their basic qualitative and quantitative research skills, facility with modern tools for acquiring and transmitting data, breadth of access to data, and ability to apply effective statistical methodology for their research. We will accomplish this through our provision to each REC investigator the full range of collaborative assistance and support including one-on-one consultation, access to data management infrastructure, didactic training, and seminars.

In addition, as member of the national RCMAR Analysis Core Network, we are committed to the sharing of educational resources such that the collective methodological expertise across centers could be made available to faculty and RCMAR Scientists more broadly as they develop their careers and research in minority aging. To do so, we have started a library of methodological lectures and manuals developed by members of our core and invited speakers. More topics will be added as they become available.


Name of Presenter

Media Form











Working with a Statistician

Jeannie-Marie Leoutsakos










Baseline Imbalance & Randomized Trials

Josh Betz










Translate theory into testable hypothesis

Qian-Li Xue










Latent class analysis

Qian-Li Xue




Issues in analysis of disability data: an overview of data reduction

Qian-Li Xue










An Overview of Qualitative Research Design and Analysis

Marcela Blinka









Stop Peeking! (At Your Data) Or Do it Better

Jeannie-Marie Leoutsakos




A user’s manual for analyzing discrete-time survival data

Qian-Li Xue




Overview of key concepts of missing data issues in gerontological research

Qian-Li Xue




Growth Mixture Modeling

Jeannie-Marie Leoutsakos


Fitting multilevel models with heteroskedastic errors

Qian-Li Xue




A Practical Guide to the Selection, Analysis, and Interpretation of Longitudinal Models

Qian-Li Xue




Exploring the Longitudinal Relationship between Depression and Pain in Knee Osteoarthritis

Michelle Shardell