1.      Huang, Y., Liang H., Wu, H. (2008) Identifying predictors for anti-HIV treatment response: mechanism-based differential equation models versus empirical semiparametric regression models. Statistics in Medicine. (in press)

2.      Huang, Y. (2008) Long-term HIV dynamic models incorporating drug adherence and resistance to treatment for prediction of virological responses. Computational Statistics and Data Analysis. 52, 3765-3778.

3.      Huang, Y., Wu, H. (2008). Bayesian experimental design for long-term longitudinal HIV dynamic studies. Journal of Statistical Planning and Inference. 138, 105-113.

4.      Brown, C. H, Costigan, T. E., Kendziora, K. (2008). Data analytic frameworks: Analysis of variance, latent growth and hierarchical models.  In Nezu & Nezu (Eds) Evidence-based outcome research: A practical guide to conducting randomized clinical trials for psychosocial interventions. London: Oxford University Press, 285-313.

5.      Brown CH, Guo J, Singer T, Downes K, and Brinales JM. (2008). Examining the effects of school-based drug prevention programs on drug use in rural settings: methodology and initial findings. J Rural Health. (in press)

6.      Kellam, SG, Brown, CH, Poduska, J, Ialongo, N, Wang, W, Toyinbo, P, Petras, H, Ford, C, Windham, A, Wilcox, HC. (2008). Effects of a universal classroom behavior management program in first and second grades on young adult behavioral, psychiatric, and social outcomes.  J Drug and Alcohol Dependence Special Issue on Prevention. (in press)

7.      Brown, C. H, Costigan, T. E., and Kendziora, K. (2008). Data analytic frameworks: Analysis of variance, latent growth and hierarchical models.  In Nezu & Nezu (Eds) Evidence-Based Outcome Research: A Practical Guide to Conducting Randomized Clinical Trials for Psychosocial Interventions (pp. 285-313). London: Oxford University Press, 285-313.

8.      Brown CH, Wyman PA, Brinales JM, and Gibbons RD (2008). The role of randomized trials in testing interventions for the prevention of youth suicide. International Journal of Psychiatry. (in press)

9.      Poduska J, Kellam SG, Wang W, Brown CH, Ialongo N, Toyinbo P, (2008). Impact of the good behavior game, a universal classroom–based behavior intervention, on young adult service use for problems with emotions, behavior, or drugs or alcohol. Drug and Alcohol Dependence. (in press)

10.  Brown, CH., Wang, W., Kellam, SG., Muthén, BO. et al. (2008). Methods for testing theory and evaluating impact in randomized field trials: intent-to-treat analyses for integrating the perspectives of person, place, and time. J Drug and Alcohol Dependence Special Issue on Prevention. (in press )

11.  Chamberlain, P,  Brown, CH., Saldana, L., Reid, J., Wang, W., Marsenich, L., Sosna, T., Padgett, C., and Bouwman, G. (2008). Engaging and recruiting counties in an experiment on implementing evidence-based practice in California. Administration and Policy in Mental Health and Mental Health Services Research. (in press)

12.  Dagne, G. A. (2008). Multi-class models for correlated zero-inflated count data. Far East J. Theoretical Statistics. (in press)

13.  Das TK, Savachkin AA, and Zhu, Y. (2008). A large scale simulation model of pandemic Iinfluenza outbreaks for development of dynamic mitigation strategies. IIE Transactions. (in press)

14.  Huang, Y. (2007). Modeling the short-, middle- and long-term viral load responses for comparing estimated dynamic parameters. Biometrical Journal.49, 429-440.

15.  Carter J. D., Lodhi A., Nagda S., Traina E., Ricca L., Ward C., Thompson Z., Huang Y., Valeriano J., Vasey F. (2007). Determining Rheumatologists’ accuracy at assessing functional disability in Rheumatoid arthritis patients using the health assessment questionnaire—disability index (HAQ-DI). Journal of Rheumatology. 34, 958-963

16.  Huang, Y., Wu, H. (2007) HIV dynamic modeling and prediction of clinical outcomes in AIDS clinical research. Part II: Epidemiology in Statistical Advance in the Biomedical Sciences: Clinical Trials, Epidemiology, Survival Analysis and Bioinformatics. Edited by Atanu Biswas, Sujay Datta, Jason Fine and Mark Segal. New York: John Wiley & Sons, Inc. November 2007. 83—96.

17.  Brown CH, Kellam SG, Ialongo N, Poduska J, Ford C. (2007). Prevention of aggressive behavior through middle school using a first grade classroom-based intervention. In Tsuang MT, Lyons MJ, Stone WS (Eds). Recognition and Prevention of Major Mental and Substance Abuse Disorders (American Psychopathological Association Series) Arlington, VA: American Psychiatric Publishing, Inc, 347-370.

18.  Gibbons RD, Brown CH, Hur K, Marcus S, Bhaumik DK, and Mann JJ (2007).  The relationship between antidepressants and suicide: Results of analysis of the Veterans Health Administration Datasets.  Amer J Psychiatry, 164, 1044-1049.

19.  Gibbons RD, Brown CH, Hur K, Marcus S, Mann JJ, Erkens J,  and Herings R (2007).  Early Evidence on the Effects of the Regulators’ Suicidality Warnings on SSRI Prescription and Suicide in Children and Adolescents.  Amer J Psychiatry, 164, 1356-1363.

20.  Dagne G. A., Brown C. H., and Howe G.W. (2007). Hierarchical modeling of sequential behavioral data: Log-linear extensions to study complex association patterns in mediation models. Psych Methods. (in press)

21.  MacKinnon, DP, Lockwood, CM, Brown, CH, Wang, W, Hoffman, JM (2007). The intermediate endpoint effect in logistic and probit. Clinical Trials, 4,  499-513.

22.  Hsu, JC, Chang, J, and Wang, T, Steingrímsson, E, Magnússon, MK, Bergsteinsdottir, K (2007). Statistically designing microarrays and microarray experiments to enhance sensitivity and specificity.  Briefings in Bioinformatics, 8, 22-31.

23.  Zhu, Y, Wang, T, Jelsovsky, JZH (2007). Bootstrap estimation of benchmark doses and confidence limits with clustered quantal data. Risk Analysis, 27, 447–465.

24.  Wu. Y., Zhu. Y. and Wang W. (2007). Impact of misclassifcation on average run length of CUSUM charts with application to syndromic surveillance. Statistics and Probability Letter. ??, ??-??

25.  Huang, Y. and Wu, H. (2006). A Bayesian approach for estimating antiviral efficacy in HIV dynamic model. Journal of Applied Statistics. 33, 155-174.

26.  Huang, Y. Liu, D and Wu, H. (2006). Hierarchical Bayesian methods for estimation of parameters in a longitudinal HIV dynamic system. Biometrics. 62, 413-423.

27.  Wu, H., Huang, Y., et al. (2006). Modeling and estimation of replication fitness of HIV-1 in vitro experiments using growth competition assay. Journal of Virology. 80, 2380-2389.

28.  Wu, H., Huang, Y., Acosta, P. E, Rosenkranz S.L., …, Perelson, A.S, Gerber, J.G. (2006). Pharmacodynamics of antiretroviral agents in HIV-1 infected patients using viral dynamic models with consideration of drug susceptibility and adherence. Journal of Pharmacokinetics and Pharmacodynamics. 33, 399-419.

29.  Dykes, C., Jiong Wang, Xia, J., Huang, Y., Wu, H., Demeter, L. M. (2006). Evaluation of a multiple-cycle, recombinant virus growth competition assay that uses flow cytometry to measure replication Efficiency of HIV-1 in Cell Culture. Journal of Clinical Microbiology . 44, 1930-1943.

30.  Hsu, JC, Chang, J, and Wang, T (2006). Simultaneous confidence intervals for differential gene expressions. Journal of Statistical Planning and Inference, 136, 2182-2196.

31.  Hsu, JC, Chang, J, and Wang, T (2006). Multiple comparisons in screening for differential gene expressions from microarray data screening: Methods for experimentation in industry, drug discovery, and denetics. Angela Dean and Sue Lewis (Eds), Chapter 6, Springer Verlag, 139-155.

32.  Snyder, J.,  John Reid, J., Stoolmiller, M., Howe, G., Brown, H., Dagne, G. A., and Cross, W. (2006). The Role of behavior observation in measurement systems for randomized prevention trials. Prevention Science, 7, 43-56.

33.  Hlaing WM, Prineas RJ, & Zhu Y (2006). Growth trajectory of systolic blood pressure (SBP) in children and adolescents. Annals of Epidemiology, 16 (1), 11-18.

34.  Howe, GW, Dagne, G.A., and Brown, CH (2005). Multilevel methods for modeling observed sequences of family interaction.  Journal of Family Psychology, 19, 72-85.

35.  Brown C. H. & Sturgeon S (2005).  Promoting a healthy start in life and dealing with early risks.  In C Hosman, E Jane-Llopis & S Saxena (Eds.), Prevention of Mental Disorders: Effective Interventions and Policy Options.  Oxford: Oxford University Press.

36.  Huang, Y. (2005). On a family of interval estimators of effective doses. Computational Statistics and Data Analysis. 49, 131-146.

37.  Wu, H., Huang, Y., Acosta, P. E., Rosenkranz S.L., …, Perelson, A.S, Gerber, J.G. (2005). Modeling long-term HIV dynamics and antiretroviral response: effects of drug potency, pharmacokinetics, adherence and drug resistance. JAIDS. 39, 272-283.

38.  Huang, Y. and Wu, H. (2005). Bayesian estimation of individual parameters in an HIV dynamic model using long-term viral load data. Chapter 15 in Deterministic and Stochastic Models of AIDS Epidemics and HIV Infections with Intervention. Edited by W.Y. Tan and H. Wu. Singapore: World Scientific. 361-383.

39.  Zhu, Y. (2005). Dose-time-response modeling of longitudinal measurements for neurotoxicity risk assessment. Environmetrics 16, 603-617.

40.  Zhu, Y, Jia, Z, Wang, W, Gift, J, Moser, V, Pierre-Louis, B. (2005). Analyses of neurobehavioral screening data: Benchmark dose estimation. Regulatory Toxicology and Pharmacology, 42, 190-201.

41.  Zhu, Y, Wang, W, Atrubin, D. and Wu, Y. (2005). Initial evaluation of the early aberration reporting system. MMWR. 54:S3, 123.

42.  Zhu, Y., Wessel, M.R., Liu, T., and Moser, V.C. (2005). Analyses of neurobehavioral screening data: Dose-time-response modeling of continuous outcomes. Regulatory Toxicology and Pharmacology 41, 240-255. 

NIMH/NIDA R01: C Hendricks Brown (PI)	2005-2009	50% efforts
Methodology for Mental Health and Drug Abuse Prevention and Early Intervention The major goal of this project is to extend the current work by developing an integrated set of new statistical models, Multilevel Growth Mixture Models, that incorporate person-level, time, and context in the same methodology.  We also present new statistical designs for randomized field trials and incorporate nonlinear “additive” models.  A second aim focuses on designs and analyses for low baserate disorders, including suicide, psychosis, and drug abuse/dependence.  The third aim will focus on the designs and analyses specifically appropriate for implementing interventions with communities.  We will develop new designs for implementation trials, including trials outside a trial and trials after a trial.

NIH/NIMH P20: E. Caine (PI), C H. Brown (Co-PI)	2004-2009	2% efforts
Developing Center On Public Health And Population Interventions For The Prevention Of Suicide This application represents a collective vision for public health and population-oriented approaches to preventing suicide and attempted suicide, and the morbidity arising from myriad associated risk factors.  The PHP-Center develops new theories of prevention, using novel research designs and measures, and extends the application of new theoretical and analytic approaches to suicide prevention and intervention research, and, carries out high quality investigations that move forward efforts to reduce the mortality and morbidity of suicide, attempted suicide, and related antecedent conditions.

NIH/NIMH P30: I. Sandler (PI), C. H. Brown (Co-I)	2005-2009	4% efforts
ASU Prevention Research Center for Families in Stress The Center focuses on preventive interventions for children who are at risk for developing mental health problems because of exposure to high stress situations; parental divorce, parental death and inner city, Mexican American children in transition to high school. The overall objective of the application is to make the transition from University based studies of the efficacy of preventive interventions to the effectiveness of programs as implemented in community agencies. Concepts and methods from service marketing, quality management and educational design are used to redesign the programs so that they can be readily implemented in community agencies. The Research Methods Core develops collaborative workgroups of methodologists and substantive researchers to focus on five methodological issues: measurement, variability in outcomes, implementation and compliance with interventions, multilevel data, and economic analysis.

NIH/NIMH R01: P.Chamberlain(PI), C.H. Brown(Co-PI)	2006-2011	10% efforts
Community Development Teams to Scale-Up MTFC in California We propose to test the effectiveness of the Community Development Team (CDT), a theory-driven model to promote the adoption, implementation, and sustainability of one such intervention (Multidimensional Treatment Foster Care; MTFC) in California counties that are not already using MTFC. To examine the effectiveness of the CDT intervention, counties will be randomly assigned to the CDT plus Standard Implementation of MTFC (CDT) condition, or to the Standard Implementation of MTFC only (SI) condition. The CDT intervention model was developed in an effort to engage and support evidence-based programming throughout the state. We will test whether a set of fixed contextual factors moderate the hypothesized intervention effect. Additionally, we will examine whether changes in a set of dynamic contextual factors mediate the association between random assignment and the intervention effects.

NIH/NIMH R56: R. Gibbons (PI), C. H. Brown (Co-PI)	2006-2007	5% efforts
Antidepressant Treatment and Suicidality: Biostatistical/Methodological Solutions The purpose of this proposal is to develop, test, and apply new statistical design and analytical methodologies that can be used to identify low base rate drug - adverse event (AE) interactions. These new methods will then be applied to examine the relationship between SSRIs and suicide ideation, attempts, and completion. The first set of aims will lead to the development of new biostatistical methods for identifying drug-AE interactions using both spontaneous (SRS) and active reporting systems (ARS), addressing selection and reporting bias in electronic medical record databases, and develop statistical methods for large-scale drug-AE screening. The second set of aims applies these methods to existing large scale databases.

NIH/NIMH R34: P. Wyman (PI), C. H. Brown (Co-PI)	2004-2008	5% efforts
RCT of Gatekeeper Training for Suicide Prevention This application to the NIMH is for testing with a randomized school-based trial a model of gatekeeper training of all staff in 32 middle and high schools in a school district in Georgia.  The QPR training program is provided in a wait-listed design to all schools.  Working closely with the school’s Prevention Intervention Center, we will evaluate whether more children with suicidal ideation and behaviors are identified, get professionally assessed and enter treatment.  Levels of suicidal ideation in 8th and 10th grades are also examined.

NSF: Y. Zhu (PI)	1999-2005	??% efforts
Statistical Innovations to Risk Assessment of Neurotoxicity To develop efficient experimental design and new statistical methods to detect and model neurotoxic risk due to exposure to environmental agents; to develop and test methods for estimating benchmark dose of neurotoxicity.

NIH/NIAID R01: H. Wu (PI), Y.Huang (Co-PI)	2003-2009	20% efforts
AIDS Clinical Trial Modeling and Simulations The major goal of this project is to combine new technologies in mathematical modeling, statistical methods, computer simulations, pharmacokinetics/pharmacodynamics, and clinical/biological sciences in HIV/AIDS research to develop simulation systems for AIDS clinical trials. We expect that the trial simulation systems can help with design of complicated AIDS clinical trials, to optimize sophisticated AIDS treatment strategies, and to study biological mechanisms of HIV infection and AIDS pathogenesis.