@article{shao_canner_everett_bekele-maxwell_kuerbis_stephenson_menda_morgenstern_banks_2023, title={A Comparison of Mathematical and Statistical Modeling with Longitudinal Data: An Application to Ecological Momentary Assessment of Behavior Change in Individuals with Alcohol Use Disorder}, volume={85}, ISSN={["1522-9602"]}, DOI={10.1007/s11538-022-01097-1}, abstractNote={Ecological momentary assessment (EMA) has been broadly used to collect real-time longitudinal data in behavioral research. Several analytic methods have been applied to EMA data to understand the changes of motivation, behavior, and emotions on a daily or within-day basis. One challenge when utilizing those methods on intensive datasets in the behavioral field is to understand when and why the methods are appropriate to investigate particular research questions. In this manuscript, we compared two widely used methods (generalized estimating equations and generalized linear mixed models) in behavioral research with three other less frequently used methods (Markov models, generalized linear mixed-effects Markov models, and differential equations) in behavioral research but widely used in other fields. The purpose of this manuscript is to illustrate the application of five distinct analytic methods to one dataset of intensive longitudinal data on drinking behavior, highlighting the utility of each method.}, number={1}, journal={BULLETIN OF MATHEMATICAL BIOLOGY}, author={Shao, Sijing and Canner, Judith E. E. and Everett, Rebecca A. and Bekele-Maxwell, Kidist and Kuerbis, Alexis and Stephenson, Lyric and Menda, Jennifer and Morgenstern, Jon and Banks, H. T.}, year={2023}, month={Jan} }
 @article{banks_bekele-maxwell_everett_stephenson_shao_morgenstern_2017, title={Dynamic Modeling of Problem Drinkers Undergoing Behavioral Treatment}, volume={79}, ISSN={["1522-9602"]}, DOI={10.1007/s11538-017-0282-5}, abstractNote={We use dynamical systems modeling to help understand how selected intra-personal factors interact to form mechanisms of behavior change in problem drinkers. Our modeling effort illustrates the iterative process of modeling using an individual's clinical data. Due to the lack of previous work in modeling behavior change in individual patients, we build our preliminary model relying on our understandings of the psychological relationships among the variables. This model is refined and the psychological understanding is then enhanced through the iterative modeling process. Our results suggest that this is a promising direction in research in alcohol use disorders as well as other behavioral sciences.}, number={6}, journal={BULLETIN OF MATHEMATICAL BIOLOGY}, author={Banks, H. T. and Bekele-Maxwell, Kidist and Everett, R. A. and Stephenson, Lyric and Shao, Sijing and Morgenstern, Jon}, year={2017}, month={Jun}, pages={1254–1273} }