Many well-thought-out research studies fail to answer the questions they pose because of a lack of planning for appropriate study design and subsequent analysis.
I’m passionate about providing optimal design and analysis plans for such projects, so that the results of the study clearly answer the questions posed. My research focuses on the design and analysis of correlated data, particularly high-dimensional data obtained from neuroimaging studies such as MRI, functional MRI (fMRI), diffusion tensor imaging (DTI) and magnetic resonance spectroscopy (MRS).
I have been a researcher for more than 22 years and began my work at Cincinnati Children’s in 2001. My research is funded by the National Institutes of Health (NIH), the Centers for Disease Control and Prevention (CDC) and the Department of Defense (DoD).
One of my significant research contributions was the development of the first infant brain template used to make inferences about neuroimaging research (2008). Since then, many researchers have downloaded this template for use in their studies.
In addition to authoring and co-authoring more than 150 peer-reviewed publications and a book chapter, I have presented my work at national meetings.
I’m currently the director of the Data Management and Analysis Center within the Division of Biostatistics and Epidemiology at Cincinnati Children’s. In this role, — where I often work with other biostatisticians, epidemiologists and informaticists — I enjoy helping others, solving problems and making sense of data. My work takes place in a highly collaborative environment; I partner with teams of basic and clinical scientists representing a variety of disciplines that leverage neuroimaging as part of their studies.
PhD: The University of Western Ontario, London, Canada, 1998.
MSc: Oklahoma State University, Stillwater, OK, 1991.
BSc: Addis Ababa Universtiy, Addis Ababa, Ethiopia, 1983.
Design and analysis of correlated data. This includes developing inference procedures for intraclass correlation, and kappa statistic. Modeling issues associated with high dimensional data that arise from brain imaging studies such as fMRI, MRI and DTI.
Biostatistics and Epidemiology
Yoga as an intervention to promote bone and mental health in adolescent females with anorexia nervosa: a pilot study. Eating Disorders. 2023; 31:526-532.
Killian Jamieson Diverticulum, the Great Mimicker: A Case Series and Contemporary Review. The Laryngoscope. 2023; 133:2110-2115.
Psychometric properties of inhibitory control measures among youth with Down syndrome. Journal of Intellectual Disability Research. 2023; 67:753-769.
Maternal education as an environmental factor related to reading in children with reading difficulties: A functional magnetic resonance imaging study. Dyslexia: an international journal of research and practice. 2023; 29:217-234.
Cricopharyngeus Muscle Dysfunction and Hypopharyngeal Diverticula (e.g., Zenker): A Multicenter Study. The Laryngoscope. 2023; 133:1349-1355.
Examining reaction time variability on the stop-signal task in the ABCD study. Journal of the International Neuropsychological Society : JINS. 2023; 29:492-502.
Early-Stage Glottic Carcinoma in the United States: Demographics and Treatment Choice. The Laryngoscope. 2023; 133:901-907.
Characterizing the Adolescent Premature Ovarian Insufficiency Phenotype: A Case Control Study. Journal of Pediatric and Adolescent Gynecology. 2023; 36:122-127.
Mathematics abilities associated with adaptive functioning in preschool children born preterm. Child Neuropsychology. 2023; ahead-of-print:1-14.