Intensive longitudinal data are becoming increasingly common in substance use research and HIV/AIDS research. Substance use researchers employ technological innovations such as hand-held computers, cell phones and web-based assessment to collect data in which many observations are collected closely spaced at time. These data collection approaches have revolutionized the process of scientific research and knowledge discovery in the substance use area. Additionally, many HIV/AIDS studies have become mature longitudinal studies that have collected many waves of data and have amassed many observations over the course of years of data collection. Thus, mature longitudinal data with many waves may be viewed as intensive Tongitudinal data as well. In theory, intensive longitudinal data can provide answers to important questions in drug abuse research and HIV/AIDS research. However, there are no appropriate statistical procedures that can be applied for such data to address important scientific questions, such as: What is the relationship between mood and urge to smoke over the period from quitting smoking to the first relapse? What factors predict first instance of unsafe sex after a diagnosis of HIV? In this project, we propose new models for joint analysis of intensive longitudinal data and time-to-event data. These models possess many valuable features which make them the most appropriate to use for testing key hypotheses in drug use research and HIV/AIDS research using intensive longitudinal data. The proposed new models allow effects to vary over time and changing across individual subjects, and keep the structure of random error process very flexible. We further propose estimation procedures for the proposed new models. We plan to develop software to implement the proposed procedure and assess the performance of the proposed procedures by extensive Monte Carlo simulations. We further plan to apply the new procedures we have developed to address important questions in substance use and HIV/AIDS research areas using intensive longitudinal data on HIV/AIDS and on tobacco, alcohol and marijuana.
Tobacco, alcohol and marijuana are the most widely used substances within the US and have been linked to a myriad of both short and long-term consequences. Findings in this project will help public health researchers to undertand the natural history of HIV infection, including the progression of HIV infection to AIDS, and the etiology of drug use and dependence and further inform drug use and treatment efforts.
|Li, Runze; Liu, Jingyuan; Lou, Lejia (2017) Variable Selection via Partial Correlation. Stat Sin 27:983-996|
|Piper, Megan E; Cook, Jessica W; Schlam, Tanya R et al. (2017) Toward precision smoking cessation treatment II: Proximal effects of smoking cessation intervention components on putative mechanisms of action. Drug Alcohol Depend 171:50-58|
|Piper, Megan E; Schlam, Tanya R; Cook, Jessica W et al. (2017) Toward precision smoking cessation treatment I: Moderator results from a factorial experiment. Drug Alcohol Depend 171:59-65|
|Yang, Songshan; Cranford, James A; Jester, Jennifer M et al. (2017) A time-varying effect model for examining group differences in trajectories of zero-inflated count outcomes with applications in substance abuse research. Stat Med 36:827-837|
|Espinosa-Hernández, Graciela; Vasilenko, Sara A; McPherson, Jenna L et al. (2017) Brief report: The role of three dimensions of sexual well-being in adolescents' life satisfaction. J Adolesc 55:61-65|
|Henneberger, Angela K; Coffman, Donna L; Gest, Scott D (2017) The Effect of Having Aggressive Friends on Aggressive Behavior in Childhood: Using Propensity Scores to Strengthen Causal Inference. Soc Dev 26:295-309|
|Yang, Songshan; Cranford, James A; Li, Runze et al. (2017) A time-varying effect model for studying gender differences in health behavior. Stat Methods Med Res 26:2812-2820|
|Vasilenko, Sara A (2017) Age-varying associations between nonmarital sexual behavior and depressive symptoms across adolescence and young adulthood. Dev Psychol 53:366-378|
|Odgers, Candice L; Russell, Michael A (2017) Violence exposure is associated with adolescents' same- and next-day mental health symptoms. J Child Psychol Psychiatry 58:1310-1318|
|NeCamp, Timothy; Kilbourne, Amy; Almirall, Daniel (2017) Comparing cluster-level dynamic treatment regimens using sequential, multiple assignment, randomized trials: Regression estimation and sample size considerations. Stat Methods Med Res 26:1572-1589|
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