Publications

Functions from the TWANG package have been used in each of the below publications (grouped by treatment setting). Also see TWANG Tutorials.

Two Treatment Groups

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  Comparative Effectiveness of Individual Versus Family-Based Substance Use Treatment on Adolescent Self-Injurious Thoughts and Behaviors 2022

  Lynsay Ayer, Joseph D. Pane, Mark D. Godley, Daniel F. McCaffrey, Lane F. Burgette, Matthew Cefalu, Brian G. Vegetabile, Beth Ann Griffin

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  Expanding Outcomes When Considering the Relative Effectiveness of Two Evidence-Based Outpatient Treatment Programs for Adolescents 2020

  Griffin B. A., Ayer L, Pane J., et al

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  The Effectiveness of Community-Based Delivery of an Evidence-Based Treatment for Adolescent Substance Use 2011

  Sarah B. Hunter, Rajeev Ramchand, Beth Ann Griffin, Marika Booth, Daniel F. McCaffrey, Andrew R. Morral

  This study evaluates the effectiveness of motivational enhancement therapy/cognitive behavioral therapy–5 (MET/CBT-5) when delivered in community practice settings relative to standard community-based adolescent treatment.

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  Using a Cross-Study Design to Assess the Efficacy of Motivational Enhancement Therapy-Cognitive Behavioral Therapy 5 (MET/CBT5) in Treating Adolescents with Cannabis-Related Disorders 2011

  Rajeev Ramchand, Beth Ann Griffin, Marika Booth, Katherine M. Harris, Andrew R. Morral

  Youth with marijuana problems who received a research-based treatment (motivational enhancement therapy plus cognitive behavioral therapy [MET/CBT5]) had better outcomes than similar youth treated in community-based programs.

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  Quantifying the Bias Due to Observed Individual Confounders in Causal Treatment Effect Estimates 2020

  Parast L., Griffin B.A.

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  Mental Health Task-Shifting in Community-Based Organizations: Implementation, Impact, and Cost — Evaluation of the Connections to Care Program 2020

  Ayer, L. and Schultz, D., eds

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  Choosing Between Covariate-balancing and Generalized Boosted Model Propensity Scores 2017

  Setodji, C. M., McCaffrey, D. F., Burgette, L. F., Almirall, D. & Griffin, B. A.

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  A Propensity-Score-Weighted Population-Based Study of the Health Benefits of Dogs and Cats for Children 2017

  Jeremy N. V. Miles, Layla Parast, Susan H. Babey, Beth Ann Griffin, Jessica Saunders

  Counter to widely held beliefs, pet ownership does not improve children's general or psychological health.

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  The Deployment Life Study: Longitudinal Analysis of Military Families Across the Deployment Cycle2016

  Sarah O. Meadows, Terri Tanielian, Benjamin Karney, Terry L. Schell, Beth Ann Griffin, Lisa H. Jaycox, Esther M. Friedman, Thomas E. Trail, Robin L. Beckman, Rajeev Ramchand, et al.

  In 2009, RAND launched the Deployment Life Study to study military family readiness. This report presents analyses on marital relationships, family environment, psychological and behavioral health, child well-being, and military integration.

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  Estimating the Causal Effects of Modifiable, Non-Genetic Factors on Huntington Disease Progression Using Propensity Score Weighting2021

  Griffin BA, Booth M.S., Busse, M., Wild E.J., Setodji, C., Warner J.H., Sampaio, C. & Mohan, A.

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  Provision of Mental Health Services as a Quality Indicator for Adolescent Substance Abuse Treatment Facilities2014

  Rajeev Ramchand, Beth Ann Griffin, Sarah B. Hunter, Marika Booth, Daniel F. McCaffrey

  The study tested whether adolescents receiving substance abuse treatment at facilities offering full or partial mental health services have better 12-month substance use and mental health outcomes than youths at facilities with no mental health services.

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  Do Improvements in Substance Use and Mental Health Symptoms During Treatment Translate to Long-Term Outcomes in the Opposite Domain?2014

  Ramchand, R, Griffin, B.A., Slaughter, M. E., Almirall, D. & McCaffrey, D. F.

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  Assessing Operation Purple: A Program Evaluation of a Summer Camp for Military Youth2012

  Ramchand, R., Griffin, B.A., Slaughter, M. E., Almirall, D. & McCaffrey, D. F.

  To help fill the gap in the research on the effectiveness of military family support programs, a RAND study explored the curriculum, themes, and outcomes of Operation Purple, a free weeklong summer camp program for youth with a deployed parent.

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  Housing Affordability and Health Among Homeowners and Renters 2010

  Craig Pollack, Beth Ann Griffin, Julia Lynch

  People living in unaffordable housing are more likely to rate their health as poor.

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  Alternate Policing Strategies: Cost-Effectiveness of Cautioning for Cannabis Offences2017

  Shanahan, M., Hughes, C. E., McSweeney, T. & Griffin, B.A.

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  Propensity Score Estimation with Boosted Regression2015

  Lane F. Burgette, Daniel F. McCaffrey, Beth Ann Griffin

  Chapter in Propensity score analysis: Fundamentals and developments edited by Wei Pan and Haiyan Bai. Published in 2015 by Guildford Publications, Inc, New York.

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  Averaging Causal Estimators in High Dimensions2020

  Antonelli, J. and Cefalu, M.

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  Synthetic Estimation for the Complier Average Causal EffectIn Press

  Agniel D., Han B., and Cefalu M.

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  Optimally Balanced Gaussian Process Propensity Scores for Estimating Treatment Effects 2019

  Vegetabile B.G., Gillen D.L., Stern H.S.

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  Collaborative Targeted Learning Using Regression Shrinkage2017

  Mireille E. Schnitzer, Matthew Cefalu

  While the underlying theory of collaborative targeted minimum loss-based estimation is quite general, current implementations involve greedy stepwise selection of covariates into the exposure model.

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  Doubly Robust Matching Estimators for High Dimensional Confounding Adjustment 2018

  Cefalu M., Antonelli J., and Agniel D.

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  Chasing Balance and Other Recommendations for Improving Nonparametric Propensity Score Models 2017

  Griffin, B. A., McCaffrey, D. F., Almirall, D., Burgette, L. F. & Setodji, C. M.

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  Optimizing Variance-Bias Trade-Off in the TWANG Package for Estimation of Propensity Scores 2017

  Parast, L., McCaffrey, D. F., Burgette, L. F., de la Guardia, F. H., Golinelli, D., Miles, J. N. & Griffin, B. A

  This discussion highlights potentially meaningful ways to optimize propensity score machine learning methods to allow for minimal bias and less variability.

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  Model Averaged Double Robust Estimation2017

  Cefalu M., Dominici F., Arvold N., and Parmigiani G.

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  A Synthetic Estimator for the Efficacy of Clinical Trials with All-Or-Nothing Compliance 2017

  Joseph Antonelli, Bing Han, Matthew Cefalu

  Synthetic estimation is a promising approach when patient noncompliance is affecting a clinical trial.

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  Collaborative Targeted Learning Using Regression Shrinkage 2017

  Mireille E. Schnitzer, Matthew Cefalu

  While the underlying theory of collaborative targeted minimum loss-based estimation is quite general, current implementations involve greedy stepwise selection of covariates into the exposure model.

More Than Two Treatment Groups

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  A Tutorial on Propensity Score Estimation for Multiple Treatments Using Generalized Boosted Models 2013

  Daniel F. McCaffrey, Beth Ann Griffin, Daniel Almirall, Mary Ellen Slaughter, Rajeev Ramchand, Lane F. Burgette

  The use of propensity scores to control for pretreatment imbalances on observed variables in non-randomized or observational studies examining the causal effects of treatments or interventions has become widespread over the past decade.

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  Effectiveness of Treatment for Adolescent Substance Use: Is Biological Drug Testing Sufficient? 2014

  Megan S. Schuler, Beth Ann Griffin, Rajeev Ramchand, Daniel Almirall, Daniel F. McCaffrey

  The purpose of this study was to compare the relative effectiveness of three treatment modalities for adolescent substance use: biological drug screening (BDS), Motivational Enhancement Therapy-Cognitive Behavioral Therapy (MET/CBT5), and BDS combined with MET/CBT5, relative to no treatment.

Continuous Treatments

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  Nonparametric Estimation of Population Average Dose-Response Curves using Entropy Balancing Weights for Continuous Exposures 2021

  Vegetabile BG, Griffin BA, Coffman DL, Godley M, McCaffrey DF

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  Robust Estimation of the Effect of Neighborhood Socioeconomic Status on Cognitive Function 2019

  Robbins, M., Griffin, B.A., Shih, R.A. & Slaughter, M.E

Time-Varying Treatment Settings

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  Toolkit for Weighting and Analysis of Nonequivalent Groups: A Tutorial on the TWANG Shiny Application for Time-Varying Treatments2021

  Beth Ann Griffin, Ricardo Sanchez, Christopher E. Maerzluft, Matthew Cefalu, Lane F. Burgette, Daniel F. McCaffrey

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  Identifying Optimal Sequences of Individually-Tailored, Level-of-Care Placement Decisions for Adolescent Substance Use Treatment: A Novel Method Using Observational Data 2017

  Agniel, D., Almirall, D., R., Burkhart, Q., Grant, S., Hunter, S. B., Pedersen, E. R., Ramchand, R, & Griffin, B. A.

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  Developing Adaptive Interventions for Adolescent Substance Use Treatment Settings: Protocol of an Observational, Mixed-Methods Project 2017

  13. Grant, S., Agniel, D., Almirall, D., Burkhart, Q., Hunter, S. B., McCaffrey, D. F., Pedersen, E. R., Ramchand, R. & Griffin, B. A.

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  Estimating the Causal Effects of Cumulative Treatment Episodes for Adolescents Using Marginal Structural Models and Inverse Probability of Treatment Weighting 2014

  Beth Ann Griffin, Rajeev Ramchand, Daniel Almirall, Mary Ellen Slaughter, Lane F. Burgette, Daniel F. McCaffrey

  We use a marginal structural model with inverse-probability-of-treatment weighting to estimate the causal effects of cumulative treatment experiences over a period of 9 months on drug use at the end of 1-year among 2870 adolescents receiving care in community-based treatment settings.

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  Subgroups Analysis when Treatment and Moderators are Time-Varying 2013a, print; 2011, e-pub

  Almirall D., McCaffrey, D.F., Ramchand R., Murphy S.A.

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  Examining Moderated Effects of Additional Adolescent Substance Use Treatment: Structural Nested Mean Model Estimation Using Inverse-Weighted Regression with Residuals 2012

  Almirall D., McCaffrey D.F., Griffin B.A., Ramchand R., Yuen R.A., Murphy S.A.

  This article considers the problem of examining causal effect moderation using observational, longitudinal data in which treatment, candidate moderators, and putative confounders are time-varying.

Causal Mediation

Forthcoming.

Causal Moderation

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  Subgroups Analysis when Treatment and Moderators are Time-Varying 2013a, print; 2011, e-pub

  Almirall D., McCaffrey, D.F., Ramchand R., Murphy S.A.

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  Examining Moderated Effects of Additional Adolescent Substance Use Treatment: Structural Nested Mean Model Estimation Using Inverse-Weighted Regression with Residuals 2012

  Almirall D., McCaffrey D.F., Griffin B.A., Ramchand R., Yuen R.A., Murphy S.A.

  This article considers the problem of examining causal effect moderation using observational, longitudinal data in which treatment, candidate moderators, and putative confounders are time-varying.

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  Examining Moderated Effects of Additional Adolescent Substance Use Treatment 2012

  Daniel Almirall, Daniel F. McCaffrey, Beth Ann Griffin, Rajeev Ramchand, Robert A. Yuen, Susan A. Murphy

  This article considers the problem of examining causal effect moderation using observational, longitudinal data in which treatment, candidate moderators, and putative confounders are time-varying.

Omitted Variable Work

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  Expanding Outcomes When Considering the Relative Effectiveness of Two Evidence-Based Outpatient Treatment Programs for Adolescents 2020

  Griffin B. A., Ayer L, Pane J., et al

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  The Relationship Between Urban Sprawl and Coronary Heart Disease in Women 2013

  Beth Ann Griffin, Christine Eibner, Chloe E. Bird, Adria D. Jewell, Karen L. Margolis, Regina A. Shih, Mary Ellen Slaughter, Eric A. Whitsel, Matthew Allison, Jose J. Escarce

  Studies have reported relationships between urban sprawl, physical activity, and obesity, but – to date – no studies have considered the relationship between sprawl and coronary heart disease (CHD) endpoints.

Statistical Computing Guidelines

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  Best Practices in Statistical Computing 2021

  Ricardo Sanchez, Beth Ann Griffin, Joseph D. Pane, Daniel F. McCaffrey

  In this paper, we describe the key steps for implementing a code quality assurance process that researchers can follow to improve their coding practices throughout a project to assure the quality of the final data, code, analyses, and results.

Other Methods Papers

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  Comparison of Methods for Handling Covariate Missingness in Propensity Score Estimation With a Binary Exposure 2020

  Coffman D.L., Zhou J., Cai X.

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  Landmark Estimation of Survival and Treatment Effects in Observational Studies 2016

  Layla Parast, Beth Ann Griffin

  Clinical studies aimed at identifying effective treatments to reduce the risk of disease or death often require long term follow-up of participants in order to observe a sufficient number of events to precisely estimate the treatment effect.

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  Propensity Score Analysis with Survey Weighted Data2015

  Ridgeway, G., Kovalchik, S. A., Griffin, B. A. & Kabeto, M. U.

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  Assessing the Sensitivity of Treatment Effect Estimates to Differential Follow-Up Rates: Implications for Translational Research2012

  Beth Ann Griffin, Daniel F. McCaffrey, Rajeev Ramchand, Sarah B. Hunter, Marika Booth

  The authors developed a new tool for assessing the sensitivity of findings on treatment effectiveness to differential follow-up rates in the two treatment conditions being compared.

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  An Application of the Principal Stratification to Control for Institutionalization at Follow-Up in Studies of Substance Abuse Treatment Programs2008

  Beth Ann Griffin, Daniel F. McCaffrey, Andrew R. Morral

  Participants in longitudinal studies on the effects of drug treatment and criminal justice system interventions are at high risk for institutionalization. Use of principal stratification to control for institutionalization at follow-up is evaluated.

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  Interpreting Treatment Effects When Cases Are Institutionalized After Treatment2007

  Daniel F. McCaffrey, Andrew R. Morral, Greg Ridgeway, Beth Ann Griffin

  Develops a causal modeling framework for evaluating the standard approaches for addressing the confounding of the effects of ignoring institutionalization of drug treatment clients and other effects, and illustrates the results of each approach.