N. Maritza Dowling PhD

Assistant Professor

N. Maritza Dowling, PhD, is an assistant professor and biostatistician at The George Washington University School of Nursing. She received a doctorate in quantitative methods with majors in statistics and psychometrics from the University of Wisconsin-Madison. Dr. Dowling’s research focuses on measurement issues in the longitudinal assessment of cognitive decline in older adults and the application of novel statistical approaches to model the complex interplay between risk and protective factors in Alzheimer’s disease-related brain changes and biomarkers for disease prognosis. Her research also aims to optimize cognitive outcome measures for early diagnosis and patient selection in clinical studies of Alzheimer’s disease-modifying therapies.

Prior to joining GW, she served for a decade as an associate scientist in the Department of Biostatistics & Medical Informatics and co-director of the Biostatistics and Data Management Unit at the Wisconsin Alzheimer’s Disease Research Center (ADRC) where she conducted independent and collaborative methodological research designed to better understand the mechanisms underlying increased risk for Alzheimer’s disease and the neural substrates of cognitive processes that differentiate normal from pathological aging in individuals at risk of Alzheimer’s and related dementias due to heredity. 

For the next five years, she will serve as a co-investigator and lead statistician on a multi-site $10.8 million NIH-NIA funded study, “Prevention of Alzheimer’s disease in women: risks and benefits of hormone therapy.” The project will examine the differences in amyloid deposition, cerebrovascular lesions, cognitive function, mood and brain structure in women who were treated with different formulations of hormone therapy compared to placebo during early postmenopause. Presently, she is also a co-Investigator and lead statistician of another multisite $2 million study funded by the Gordon & Betty Moore Foundation to study the effect of changing the culture of care to a more patient-centered approach in improving end of life care in seriously ill and frail dialysis patients.  

Her current research also seeks to examine how digital technologies can be used to attenuate the risk of functional and cognitive decline in elderly homebound and traumatic brain injury individuals.

  • Editorial Board Member of Neurology and Neurobiology
  • Biomedical Informatics Center, School of Medicine & Health Sciences, George Washington University
  • Center for Health and Aging, Washington DC VA Medical Center
  • Center for AIDS Research (DC CFAR)
  • University of Wisconsin-Madison – PhD in Quantitative Methods, (December, 2006)
  • University of Puerto Rico-PR – Master of Science in Mathematics (December, 1987)

Refereed Journals

  • Bettcher, B.M., Gross, A., Gavett, B., Widaman, K., Fletcher, E., Dowling, N. M., Buckley, R.F., Arenaza-Urquillo, E., Zahodne, L., Hohman, T.J., Rentz, D., Mungas, D. (2019, In press). Dynamic Change of Cognitive Reserve: Associations with Changes in Brain, Cognition, and Diagnosis. Neurobiology of Aging.

  • Miller,V., Asthana,S., Black, D., Brinton,E., Budoff, M., Cedars, M., Dowling, N. M., Gleason,C.E., Hodis, N., Jayachandran, M., Kantarci11,K.,  Lobo1, R., Manson, J.E., Naftolin,F., Pal, L., Santoro, N., Taylor, H.S., Harman, S.M. (2019). The Kronos Early Estrogen Prevention Study (KEEPS): what has it taught us? Menopause: The Journal of the North American Menopause Society. https://www.ncbi.nlm.nih.gov/pubmed/30939537

  • Barzgari1, A., Sojkova, J., Dowling, N. M., Pozorski, V., Okonkwo, O., Starks, E. J., Oh, J., Thiesen, F., Wey, A., Nicholas, C. R., & Gallagher, C.L. (2018). Arterial spin labeling reveals relationships between resting cerebral perfusion and motor learning in Parkinson’s disease. Brain, Imaging, and Behavior. doi: 10.1007/s11682-018-9877-1.
  • DowlingN. M., Raykov, T., Marcoulides, G. (2018, In Press). A Method for Examining the Equating of Psychometric Scales and Tests: An Application Using Dementia Screening Tests. Educational and Psychological Measurement. https://doi.org/10.1177/0013164418775785
  • Kantarci, K., Tosakulwong, N., Lesnick, T., Zuk, S., Lowe, V., Fields, J., Senjem, M., Settell, M., Gleason, C., Dowling, N.M., Jack, C. R., Rocca, W. Miller, V. (2018, In Press). Brain Structure and Cognition Three Years after an Early Menopausal Hormone Therapy Trial.  JAMA Neurologyhttp://dx.doi.org/10.1212/WNL.0000000000005325
  • **Featured Article in Neurology Today, Vol 18, April 5, 2018. https://journals.lww.com/neurotodayonline/Fulltext/2018/04050/In_the_Clinic_Cognition__The_Latest_Study_on.1.aspx
  • DowlingN. M., RaykovT., Marcoulides, G. (2018). Examining Population Differences in Within-Person Variability in Longitudinal Designs Using Latent Variable Modeling: An Application to the Study of Cognitive Functioning of Older Adults. Educational & Psychological Measurement. http://journals.sagepub.com/doi/abs/10.1177/0013164418758834
  • Bolt, D.M., Dowling, N. M., Shih, Y-S., Loh, W-Y. Using Blinder-Oaxaca Decomposition to Explore Differential Item Functioning: Application to PISA 2009 Reading, (2017, In Press, Book Chapter). Test Fairness in the New Generation of Large-Scale Assessment.
  • Dowling, N. M., Bolt, D. M., Deng, S., Li, C. (2016) Measurement and Control of Bias in Patient-Reported Outcomes Using Multidimensional Item Response Theory Models. BMC Medical Research Methodology. doi: 10.1186/s12874-016-0161-z.
  • Dowling, N. M., Bolt, D. M., Deng, S. (2016). An Approach for Item Sensitivity to Within-Person Change Over Time: An Illustration Using the ADAS-Cog. Psychological Assessment. doi.org/10.1037/pas0000285.
  • Kantarci, K., Tosakulwong, N., Lesnick, T., Zuk, S., Gunter, J., Gleason, C., Dowling, N. M., Vemuri, P., Senjem, M., Shuster, L.T., Bailey, K.R., Rocca, W., Jack, C., Asthana, S., & Miller, V. M. (2016). Effects of Hormone Therapy on Brain Structure in Post-Menopausal Women: A Randomized Controlled Trial. JAMA Neurology, 38, 887-896. doi: 10.1212/WNL.0000000000002970.
  • Miller, V. M., Raz, L., Hunter, L., Dowling, N. M., Wharton, W., Gleason, C.; Jayachandran, M.; Anderson, L. (2016). Differential Effects of Hormone Therapy on Platelet Serotonin and Mood in Women of the KEEPS. Climacteric, 9, 49-59.
  • Gleason, C, Dowling, N. M., Flowers, S., Kaseroff, A., Gunn, W., Edwards, D. (2015). Common Sense Model Factors affecting African American's disclosure of symptoms of mild cognitive impairment to providers. American Journal of Geriatric Psychiatry. doi:10.1016/j.jagp.2015.08.005.
  • Dowling, N. M., Johnson, S.C., Gleason, C.E., Jagust, W. (2015) .The Mediational Effects of FDG Hypometabolism on the Association between Cerebrospinal Fluid Biomarkers and Neurocognitive Function. NeuroImage, 105, 357-368. 
  • Li, C., Dowling, N. M., & Chappell, R. (2015). Quantile regression with a change-point model for longitudinal data: An application to the study of cognitive changes in preclinical Alzheimer's disease. Biometrics. doi: 10.1111/biom.12313.
  • Gleason, C.E, Dowling, N. M., Wharton, W., Manson, J.E., Miller, V.M., Atwood, C.S., Brinton, E.A., Cedars, M., Lobo, R.A., Merriam, G.R., Neal-Perry, G., Santoro, N.F., Taylor, H.S., Black, D.M., Budoff, M.J., Hodis, H.N., Naftolin, F., Harman, S.M. (2015). Effects of Hormone Therapy on Cognition and Mood in Recently Postmenopausal Women: Findings from the Randomized, Controlled KEEPS-Cognitive and Affective Study.  PLoS Medicine 2(6): e1001833. 
  • Gleason, C, Fischer, B.L., Dowling, N. M., Setchell, K.R., Carlsson, C.M., Asthana, S. (2015). Cognitive effects of soy isoflavones in patients with Alzheimer’s disease. Journal of Alzheimer’s Disease, 47, 1009-1019.
  • Almeida, R.P., Schultz, S., Austin, B., Boots, E., Dowling, N. M., Gleason, C.E., Bendlin, B.B., Sager, M.A., Hermann, B.P., Zetterberg, H., Carlsson, C.M., Johnson, S.C., Asthana, S., & Okonwo, O.C. (2015). Effect of cognitive reserve as a modifier of age-related changes in CSF biomarkers of Alzheimer's disease. JAMA Neurology, 72, 699-706.
  • Doherty, B., Schultz, S., Oh, J., Koscik, R., Dowling, N. M., Barnhart, T.E.,  Gallagher, C.L., Carlsson, C.M., Bendlin, B.B., LaRue, A., Hermann, B.P., Rowley, H.A., Asthana, S., Sager, M.A., Okonwo, O.  (2015). Amyloid burden, cortical thickness, and cognitive function in the Wisconsin Registry for Alzheimer’s Prevention. Alzheimer’s & Dementia: Diagnosis, Assessment, and Disease Monitoring, 1, 160-169. 
  • Dowling, N. M., Gleason,C.E, Manson, J.E., Hodis, H.N., Miller, V.,  Brinton, E.A., Neal-Perry, G., Santorro, N., Wharton,W., Cedars, M., Lobo, R, Merriam, G., Naftolin, F., Taylor, H., Harman, S.M., Asthana, S. (2014). Characterization of Vascular Disease Risk in Postmenopausal Women and its Association with Cognitive Performance. PLoS One, 8(7), e68741. 
  • Okonkwo, O., Xu, G., Oh, J., Dowling, N. M., Carlsson, C.M., Gallagher, C.L., Birdsill, A.C., Palotti, M., Wharton, W., Hermann, B.P., Larue, A., Bendlin, B.B., Rowley, H.A., Asthana, S., Sager M.A., Johnson, S. C. (2014). Cerebral Blood Flow is Diminished in Asymptomatic Middle-Aged Adults with Maternal History of Alzheimer's Disease. Cerebral Cortex, 24, 978-988.
  • Wharton, W., Gleason,C.E, Dowling, N. M., Carlsson, C, Brinton, E.A., Santoro, M.N., Neal-Perry, G., Taylor, H., Naftolin, F., Lobo, RA, Merriam, G, Manson, J.E., Cedars, M.I., Miller, V.M., Black, D. M., Budoff, M., Hodis, H. N., Harman, S. M. (2014). The KEEPS-Cognitive and Affective Study: Baseline Associations between Vascular Risk Factors and Cognition. Journal of the Alzheimer’s Disease, 40, 331-341.
  • Dowling, N. M., Olson, N., Mish, T., Kaprakattu, P., & Gleason, C. (2012). A Model for the Design and Implementation of a Participant Recruitment Registry for Clinical Studies of Older Adults. Clinical Trials: Journal of the Society for Clinical Trials, 9, 204-214.
  • Stricker, N., Dodge, H., Dowling, N.M., Han, D., Erosheva, E., Jagust, W. (2012). CSF biomarker associations with change in hippocampal volume and precuneus thickness: implications for the Alzheimer’s pathological cascade. Brain, Imaging, and Behavior Journal, 6, 599-609. 
  • Hinrichs, C., Dowling, N.M., Johnson, S.C., & Singh, V. (2012). MKL-based sample enrichment and customized outcomes enable smaller AD clinical trials. Machine Learning and Interpretation in Neuroimaging (MLINI) 2011, Lecture Notes in Artificial Intelligence (LNAI) 7263, pp. 124-131.
  • Gleason, C.E., Dowling, N.M., Friedman, E., Wharton, W., & Asthana, S. (2012). Using predictors of hormone therapy use to model the healthy user bias: How does healthy user status influence cognitive effects of hormone therapy? Menopause, 9, 524-533.

Book Chapters

Bolt, D.M., Dowling, N. M., Shih, Y-S., Loh, W-Y. Using Blinder-Oaxaca Decomposition to Explore Differential Item Functioning: Application to PISA 2009 Reading, (2017, In Press, Book Chapter). Test Fairness in the New Generation of Large-Scale Assessment.