Dr. Gueorguieva was born in 1971 in Sofia, Bulgaria in the family of engineers. She completed her undergraduate studies at Sofia University in 1994, then obtained M.Stat. and Ph.D. degrees in Statistics from the University of Florida in 1996 and 1999 respectively. Her dissertation topic was models for joint analysis of outcomes of different types under the direction of Prof. Alan Agresti. Since 2000, Dr. Gueorguieva has been a faculty in the Department of Biostatistics at Yale School of Public Health where she is currently Senior Research Scientist. She is also the Director of Biostatistics in Psychiatry in the Department of Psychiatry at Yale School of Medicine. Dr. Gueorguieva has published more than 140 peer-reviewed manuscripts, has more than 100 abstracts and conference presentations, and has been a key personnel on multiple grants funded by the National Institutes of Health in the USA.
Education
M.Sc., Informatics, Sofia University, Bulgaria, 1994
M.Stat., Statistics, University of Florida, USA, 1996
Ph.D., Statistics, University of Florida, USA, 1999
Areas of Research / Professional Expertise
Dr. Gueorguieva's methodological work is in development and application of statistical models for longitudinal data and outcomes of different types, assessment of predictors and moderators of treatment response, and use of innovative statistical approaches for design and analysis of clinical trials and observational data. She has made contributions to statistical methodology development and popularization of modern statistical approaches, and has participated in high impact collaborative research efforts in psychiatry and related fields. In particular, Dr. Gueorguieva developed extensions of models for longitudinal data for repeatedly measured discrete and continuous responses and demonstrated the advantages of the joint modeling approach in terms of efficiency and bias reduction. She has also spearheaded methodological and collaborative work focused on identification of predictors of outcome and moderators of treatment effects, including modern tree-based and machine learning approaches. Her research involving growth mixture modeling for identification of distinct trajectories over time in heterogeneous populations of individuals has been widely cited. Other research projects for which she has served as a senior author are the development of algorithms for estimation in correlated probit models and the analysis of zero-inflated count data in tobacco research.

Dr. Gueorguieva has mentored many students, post-doctoral associates and junior faculty on statistical methods in research design and analysis. She has also taught full-length and short courses in applied regression analysis, categorical data analysis, introduction to statistics and biostatistics. Her goals are to popularize and make more accessible sophisticated statistical methods that are necessary for proper analysis. Dr. Gueorguieva’s book titled “Statistical Methods in Psychiatry and Related Fields: Longitudinal, Clustered and Other Repeated Measures Data” published by Chapman and Hall/CRC Press covers mixed and mixture models, nonparametric methods, multiplicity corrections, adjusting for covariates, assessment of moderator and mediator effects, and study design. Online materials (program code, data and output) are available on the associated website . The book presents sophisticated statistical methods at a non-technical level and is a valuable resource to researchers and applied statisticians using these methods in psychiatry and other fields.
Personal Interests
Ralitza likes reading, traveling and spending time with her family.
Websites