Andrzej T. Galecki, M.D., Ph.D.
    Research Professor, Division of Geriatrics/Institute of Gerontology, Medical School
    Research Scientist,  Department of Biostatistics, School of Public Health


My research interests are in the development and application of modern statistical methods in research studies in gerontology and geriatrics. My primary interests lie in developing computational methods for analyzing correlated and overdispersed data, which are frequently encountered in many fields of application, such as pharmacokinetic and pharmacodynamic (PK/PD) studies, longitudinal studies, survey sampling and gene mapping in genetics studies.

A class of models considered in this context are hierarchical or mixed effects models.These models are an extension of the regression models whereby random effects are introduced to describe between-subject variaton.

My particular interests related to mixed effects models lie in:

  1. An extension of mixed models which allows between-subject variation to be modeled as a mixture of underlying distributions. This type of model can be applied to interval and composite gene mapping of quantitative and qualitatitive trait loci in experimental animal crosses. It is a topic within my training grant awarded by Claude Pepper Older Americans Independence Center.
  2. Computational methods for advanced PK/PD population studies. Here models are often expressed as a solution of a system of an ordinary differential equations. To address these problems a new SAS/IML NLMEM macro has been developed and sucessfully used to analyze existing data. Specific application of these models occurs in population studies when intravenous glucose tolerance test (IVGTT) studies are used to evaluate glucose metabolism in patients.
  3. Modelling covariance structure in the presence of two or more repeated factors. A class of models proposed in Galecki, 1994 has been implemented in PROC/MIXED, which is part of commercial statistical software SAS 6.12. The proposed class of covariance structures is especially useful for the analysis of several outcomes measured over time.

My other research interests involve a wide range of methodological and practical aspects of research on elderely including study design and conducting study itself. I am involved in a number of large NIH funded projects including analysis cores at the Claude D. Pepper Older Americans Independence Center and Genetics of Age-Sensitive Traits in Mice P01 project. Other involvements include using statistical methods to identify implausible records in large datasets.