Analysis of Count Data with Structural Zeros: CTN0018 and CTN0019 Project Summary/Abstract This application addresses two statistical issues in substance abuse research (1) the analysis of a count response with structural zeros, and (2) analysis of treatment moderators under a new moderation framework. Both of these statistical issues are highly relevant to the analysis of differential treatment effectiveness of HIV sexual risk interventions as examined within two NIDA Clinical Trials Network (CTN) studies: CTN0018 ("HIV/STD Safer Sex Skills Groups For Men In Methadone Maintenance Or Drug-free Outpatient Treatment Programs") and CTN0019 ("HIV/STD Safer Sex Skills Groups For Men In Methadone Maintenance Or Drug-free Outpatient Treatment Programs"). Our general goals in this application are to (1) develop new statistical methods for analysis of count data with structural zeros, (2) develop new statistical methods of analysis of moderators, (3) create software for implementing the new statistical methods, and (4) test hypotheses about moderators of treatment effectiveness using pooled data from CTN0018 and CTN0019. Specifically, we will develop a distribution-free, varying-coefficient class of models for moderation analysis of count data in the presence of structural zeros and over dispersion. This new approach addresses fundamental flaws in current methods that contribute to inconsistent findings in substance abuse and related research. We will examine two primary variables (severity of current drug use and engagement in sex under the influence of drugs/alcohol), and several secondary variables, as moderators of the effectiveness of a five session gender-specific HIV sexual skill intervention relative to a one session "treatment as usual" standard HIV education intervention. We hypothesize that (1) the five session gender-specific skills training interventions used in CTN0018 and CTN0019 will have greater effectiveness, relative to the one session standard intervention, for patients with higher levels of current drug use of their primary drug of abuse (but equal effectiveness for lower levels of current drug use), and (2) the five session intervention will have greater effectiveness, relative to the one session intervention, for patients who engage in sex under the influence of drugs/alcohol (but equal effectiveness for patients who do not engage in sex under the influence). The pooled study database will also allow for sufficient statistical power for testing of gender and minority status as potential moderators of treatment effectiveness.

Public Health Relevance

Analysis of Count Data with Structural Zeros: CTN0018 and CTN0019 Project Narrative This application develops new methods for addressing two statistical issues in substance abuse research: (1) the analysis of a count response with structural zeros, and (2) analysis of treatment moderators under a new moderation framework. Both of these statistical issues are highly relevant to the analysis of differential treatment effectiveness of HIV sexual risk interventions. The new methods will have broad applicability for the accurate analysis of data from studies of substance abuse treatments and studies of HIV risk behavior, as well as other domains of research, and will help us understand whether HIV sexual risk behavior interventions work equally well for patients with different characteristics, allowing for such interventions to be efficiently implemented in clinical practice.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Exploratory/Developmental Grants Phase II (R33)
Project #
5R33DA027521-04
Application #
8306176
Study Section
Special Emphasis Panel (ZDA1-NXR-B (02))
Program Officer
Walton, Kevin
Project Start
2009-08-15
Project End
2013-07-31
Budget Start
2012-08-01
Budget End
2013-07-31
Support Year
4
Fiscal Year
2012
Total Cost
$340,435
Indirect Cost
$79,757
Name
University of Rochester
Department
Biostatistics & Other Math Sci
Type
Schools of Dentistry
DUNS #
041294109
City
Rochester
State
NY
Country
United States
Zip Code
14627
Chen, Tian; Wu, Pan; Tang, Wan et al. (2016) Variable selection for distribution-free models for longitudinal zero-inflated count responses. Stat Med 35:2770-85
Tang, Wan; Lu, Naiji; Chen, Tian et al. (2015) On performance of parametric and distribution-free models for zero-inflated and over-dispersed count responses. Stat Med 34:3235-45
He, H; Wang, W J; Hu, J et al. (2015) Distribution-free Inference of Zero-inated Binomial Data for Longitudinal Studies. J Appl Stat 42:2203-2219
Gunzler, D; Tang, W; Lu, N et al. (2014) A class of distribution-free models for longitudinal mediation analysis. Psychometrika 79:543-68
Crits-Christoph, Paul; Gallop, Robert; Sadicario, Jaclyn S et al. (2014) Predictors and moderators of outcomes of HIV/STD sex risk reduction interventions in substance abuse treatment programs: a pooled analysis of two randomized controlled trials. Subst Abuse Treat Prev Policy 9:3
Yu, Q; Chen, R; Tang, W et al. (2013) Distribution-free models for longitudinal count responses with overdispersion and structural zeros. Stat Med 32:2390-405
Tang, Wan; He, Hua; Gunzler, Douglas (2012) Kernel Smoothing Density Estimation when Group Membership is Subject to Missing. J Stat Plan Inference 142:685-694
Tang, Wan; Zuo, Guoxin; He, Hua (2011) Double-smoothing for Varying Coefficient Models. J Nonparametr Stat 23:917-926
Zhang, Hui; Lu, Naiji; Feng, Changyong et al. (2011) On fitting generalized linear mixed-effects models for binary responses using different statistical packages. Stat Med 30:2562-72
Calsyn, Donald A; Crits-Christoph, Paul; Hatch-Maillette, Mary A et al. (2010) Reducing sex under the influence of drugs or alcohol for patients in substance abuse treatment. Addiction 105:100-8

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