Ariel Linden, DrPH
Research Specialist
Medicine
School of Medicine

Dr. Linden has published over 160 peer-reviewed papers and has written over 80 statistical software packages for Stata, several of which have been described in detail in articles in the Stata Journal and in other evaluation-focused journals.

• Association of Primary Care Engagement in Value-Based Reform Programs With Health Services Outcomes: Participation and Synergies.
  JAMA health forum 2022 Adler-Milstein J, Linden A, Hollingsworth JM, Ryan AM
• A regression-with-residuals method for analyzing causal mediation: The rwrmed package
  Stata Journal 2021 Linden A, Huber C, Wodtke GT
• Longitudinal participation in delivery and payment reform programs among US Primary Care Organizations.
  Health services research 2021 Adler-Milstein J, Linden A, Bernstein S, Hollingsworth J, Ryan A
• Conducting sensitivity analysis for unmeasured confounding in observational studies using E-values: The evalue package
  Stata Journal 2020 Linden A, Mathur MB, VanderWeele TJ.
• Implementing ODA from Within Stata: Implementing CTA from Within Stata: Minimizing Imbalances on Patient Characteristics Between Treatment Groups in Randomized Trials (Invited)
  Optimal Data Analysis 2020 Linden A
• Implementing ODA from Within Stata: Identifying Causal Mechanisms in Interventions (Invited)
  Optimal Data Analysis 2020 Linden A
• Implementing ODA from Within Stata: Modeling Time‐to‐Event (Survival) Data (Invited)
  Optimal Data Analysis 2020 Linden A
• Implementing ODA from Within Stata: Finding the Optimal Cut-Point of a Diagnostic Test or Index (Invited)
  Optimal Data Analysis 2020 Linden A
• Implementing CTA from Within Stata: Using CTA to Generate Propensity Score Weights (Invited)
  Optimal Data Analysis 2020 Linden A
• Implementing CTA from Within Stata: Characterizing Participation in Observational Studies (Invited)
  Optimal Data Analysis 2020 Linden A
• Implementing CTA from Within Stata: Assessing the Quality of the Randomization Process in Randomized Controlled Trials (Invited)
  Optimal Data Analysis 2020 Linden A
• Implementing ODA from Within Stata: Identifying Structural Breaks in Single-Group Interrupted Time Series Designs (Invited)
  Optimal Data Analysis 2020 Linden A
• Implementing ODA from Within Stata: Evaluating Treatment Effects in Multiple‐Group Interrupted Time Series Analysis (Invited)
  Optimal Data Analysis 2020 Linden A
• Implementing ODA from Within Stata: Evaluating Treatment Effects for Survival (Time‐to‐Event) Outcomes (Invited)
  Optimal Data Analysis 2020 Linden A
• Implementing ODA from Within Stata: Assessing Covariate Balance in Observational Studies (Invited)
  Optimal Data Analysis 2020 Linden A
• Implementing ODA from Within Stata: An Application to Dose-Response Relationships (Invited)
  Optimal Data Analysis 2020 Linden A
• Implementing ODA from Within Stata: An Application to Estimating Treatment Effects using Observational Data (Invited). 2020;9:14-20
  Optimal Data Analysis 2020 Linden A
• Implementing ODA from Within Stata: An Application to Data From a Randomized Controlled Trial (Invited)
  Optimal Data Analysis 2020 Linden A
• Assessing medication adherence using Stata
  Stata Journal 2019 Linden A
• Assessment of Self-monitoring of Blood Glucose in Individuals With Type 2 Diabetes Not Using Insulin.
  JAMA internal medicine 2019 Platt KD, Thompson AN, Lin P, Basu T, Linden A, Fendrick AM
• Effect of Sample Size on Discovery of Relationships in Random Data by Classification Algorithms
  Optimal Data Analysis 2019 Linden A, Yarnold PR
• Logistic Discriminant Analysis and Structural Equation Modeling Both Identify Effects in Random Data
  Optimal Data Analysis 2019 Linden A, Bryant FB, Yarnold PR
• Multi-layer perceptron neural net model identifies effect in random data
  Optimal Data Analysis 2019 Linden A, Yarnold PR
• Novometric stepwise CTA analysis discriminating three class Categories using two ordered attributes
  Optimal Data Analysis 2019 Yarnold PR, Linden A
• Optimizing Suboptimal Classification Trees: Matlab® CART Model Predicting Probability of Lower Limb Prosthesis User’s Functional Potential
  Optimal Data Analysis 2019 Yarnold PR, Linden A
• Some machine learning algorithms find relationships between variables when none exist -- CTA doesn’t
  Optimal Data Analysis 2019 Linden A, Yarnold PR
• Now trending: Coping with non-parallel trends in difference-in-differences analysis.
  Statistical methods in medical research 2018 Ryan AM, Kontopantelis E, Linden A, Burgess JF
• Practice strategies to improve primary care for chronic disease patients under a pay-for-value program.
  Healthcare (Amsterdam, Netherlands) 2018 Cross DA, Nong P, Harris-Lemak C, Cohen GR, Linden A, Adler-Milstein J
• Using randomization tests to assess treatment effects in multiple-group interrupted time series analysis.
  Journal of evaluation in clinical practice 2018 Linden A
• Using machine learning to evaluate treatment effects in multiple-group interrupted time series analysis.
  Journal of evaluation in clinical practice 2018 Linden A, Yarnold PR
• Using forecast modelling to evaluate treatment effects in single-group interrupted time series analysis.
  Journal of evaluation in clinical practice 2018 Linden A
• Using group-based trajectory modelling to enhance causal inference in interrupted time series analysis.
  Journal of evaluation in clinical practice 2018 Linden A
• Using permutation tests to enhance causal inference in interrupted time series analysis.
  Journal of evaluation in clinical practice 2018 Linden A
• Combining synthetic controls and interrupted time series analysis to improve causal inference in program evaluation.
  Journal of evaluation in clinical practice 2018 Linden A
• Comparative accuracy of a diagnostic index modeled using (optimized) regression vs. novometrics
  Optimal Data Analysis 2018 Linden A, Yarnold PR.
• Identifying maximum-accuracy cut-points for diagnostic indexes via ODA
  Optimal Data Analysis 2018 Linden A, Yarnold PR.
• Reanalysis of the National Supported Work Experiment Using ODA
  Optimal Data Analysis 2018 Linden A, Yarnold PR.
• Review of “A Course in Item Response Theory and Modeling with Stata” by Raykov and Marcoulides
  Stata Journal 2018 Linden A.
• The Australian gun buy-back program and the rate of suicide by firearm
  Optimal Data Analysis 2018 Linden A, Yarnold PR.
• Using ODA in the evaluation of randomized controlled trials
  Optimal Data Analysis 2018 Linden A, Yarnold PR.
• Using ODA in the evaluation of randomized controlled trials: application to survival outcomes
  Optimal Data Analysis 2018 Linden A, Yarnold PR.
• A matching framework to improve causal inference in interrupted time-series analysis.
  Journal of evaluation in clinical practice 2017 Linden A
• Estimating causal effects for survival (time-to-event) outcomes by combining classification tree analysis and propensity score weighting.
  Journal of evaluation in clinical practice 2017 Linden A, Yarnold PR
• Identifying causal mechanisms in health care interventions using classification tree analysis.
  Journal of evaluation in clinical practice 2017 Linden A, Yarnold PR
• Precommitting to choose wisely about low-value services: a stepped wedge cluster randomised trial.
  BMJ quality & safety 2017 Kullgren JT, Krupka E, Schachter A, Linden A, Miller J, Acharya Y, Alford J, Duffy R, Adler-Milstein J
• Minimizing imbalances on patient characteristics between treatment groups in randomized trials using classification tree analysis.
  Journal of evaluation in clinical practice 2017 Linden A, Yarnold PR
• Modeling time-to-event (survival) data using classification tree analysis.
  Journal of evaluation in clinical practice 2017 Linden A, Yarnold PR
• Using classification tree analysis to generate propensity score weights.
  Journal of evaluation in clinical practice 2017 Linden A, Yarnold PR
• Improving causal inference with a doubly robust estimator that combines propensity score stratification and weighting.
  Journal of evaluation in clinical practice 2017 Linden A
• A comparison of approaches for stratifying on the propensity score to reduce bias.
  Journal of evaluation in clinical practice 2017 Linden A
• A comprehensive set of post-estimation measures to enrich interrupted time series analysis
  Stata Journal 2017 Linden A.
• Computing propensity score weights for CTA models involving perfectly predicted endpoints
  Optimal Data Analysis 2017 Yarnold PR, Linden A
• Persistent threats to validity in single-group interrupted time series analysis with a cross over design.
  Journal of evaluation in clinical practice 2016 Linden A
• Challenges to validity in single-group interrupted time series analysis.
  Journal of evaluation in clinical practice 2016 Linden A
• Combining machine learning and propensity score weighting to estimate causal effects in multivalued treatments.
  Journal of evaluation in clinical practice 2016 Linden A, Yarnold PR
• Combining machine learning and matching techniques to improve causal inference in program evaluation.
  Journal of evaluation in clinical practice 2016 Linden A, Yarnold PR
• Using machine learning to model dose-response relationships.
  Journal of evaluation in clinical practice 2016 Linden A, Yarnold PR, Nallamothu BK
• Using machine learning to identify structural breaks in single-group interrupted time series designs.
  Journal of evaluation in clinical practice 2016 Linden A, Yarnold PR
• Using machine learning to assess covariate balance in matching studies.
  Journal of evaluation in clinical practice 2016 Linden A, Yarnold PR
• Using data mining techniques to characterize participation in observational studies.
  Journal of evaluation in clinical practice 2016 Linden A, Yarnold PR
• Novometric analysis with ordered class variables: The optimal alternative to linear regression analysis
  Optimal Data Analysis 2016 Yarnold PR, Linden A.
• Review of “Maximizing Predictive Accuracy By P. R. Yarnold R. C. Soltysik. ODA Books, Chicago, IL, 2016, $98.00, 396 pp. ISBN 0 692 70092 7”
  J Eval Clin Pract 2016 Linden A.
• Theoretical aspects of the D statistic
  Optimal Data Analysis 2016 Yarnold PR, Linden A.
• Using machine learning to model dose-response relationships via ODA: eliminating response variable baseline variation by ipsative standardization
  Optimal Data Analysis 2016 Yarnold PR, Linden A.
• Estimating Measurement Error of the Patient Activation Measure for Respondents with Partially Missing Data.
  BioMed research international 2015 Linden A
• Estimating causal effects for multivalued treatments: a comparison of approaches.
  Statistics in medicine 2015 Linden A, Uysal SD, Ryan A, Adams JL
• Conducting interrupted time-series analysis for single- and multiple-group comparisons
  Stata Journal 2015 Linden A.
• Graphical displays for assessing covariate balance in matching studies.
  Journal of evaluation in clinical practice 2014 Linden A
• A comprehensive hospital-based intervention to reduce readmissions for chronically ill patients: a randomized controlled trial.
  The American journal of managed care 2014 Linden A, Butterworth S
• Combining propensity score-based stratification and weighting to improve causal inference in the evaluation of health care interventions.
  Journal of evaluation in clinical practice 2014 Linden A
• Review of “An Introduction to Stata for Health Researchers, Fourth Edition, by Juul and Frydenberg.”
  Stata Journal 2014 Linden A.
• Assessing regression to the mean effects in health care initiatives.
  BMC medical research methodology 2013 Linden A
• Using balance statistics to determine the optimal number of controls in matching studies.
  Journal of evaluation in clinical practice 2013 Linden A, Samuels SJ
• Advancing current approaches to disease management evaluation: capitalizing on heterogeneity to understand what works and for whom.
  BMC medical research methodology 2013 Elissen AM, Adams JL, Spreeuwenberg M, Duimel-Peeters IG, Spreeuwenberg C, Linden A, Vrijhoef HJ
• Using mediation analysis to identify causal mechanisms in disease management interventions
  Health Services and Outcomes Research Methodology 2013 Linden A, Karlson KB.
• Estimating measurement error when annualizing health care costs.
  Journal of evaluation in clinical practice 2012 Linden A, Samuels SJ
• Combining the regression discontinuity design and propensity score-based weighting to improve causal inference in program evaluation.
  Journal of evaluation in clinical practice 2012 Linden A, Adams JL
• Identifying spin in health management evaluations.
  Journal of evaluation in clinical practice 2011 Linden A
• A successful hospital-based disease management program to reduce admissions among patients with multiple chronic illnesses
  International Journal of Person Centered Medicine 2011 Linden A, Bonollo M, Fiddes K.
• Use of an algorithm applied to urine drug screening to assess adherence to a hydrocodone regimen
  Journal of Clinical Pharmacology & Therapeutics 2011 Couto J, Webster L, Romney M, Leider H, Linden A.
• Applying a propensity score-based weighting model to interrupted time series data: improving causal inference in programme evaluation.
  Journal of evaluation in clinical practice 2010 Linden A, Adams JL
• Designing a prospective study when randomization is not feasible.
  Evaluation & the health professions 2010 Linden A
• Help patients with chronic kidney disease stave off dialysis.
  The Journal of family practice 2010 Linden A, Biuso TJ, Butterworth SW
• Evaluating health management programmes over time: application of propensity score-based weighting to longitudinal data.
  Journal of evaluation in clinical practice 2010 Linden A, Adams JL
• Motivational interviewing-based health coaching as a chronic care intervention.
  Journal of evaluation in clinical practice 2010 Linden A, Butterworth SW, Prochaska JO
• Using propensity score-based weighting in the evaluation of health management programme effectiveness.
  Journal of evaluation in clinical practice 2010 Linden A, Adams JL
• Use of an algorithm applied to urine drug screening to assess adherence to an oxycontin regimen.
  Journal of opioid management 2009 Couto JE, Webster L, Romney MC, Leider HL, Linden A
• Improving participant selection in disease management programmes: insights gained from propensity score stratification.
  Journal of evaluation in clinical practice 2008 Linden A, Adams JL
• Disease management: truth in advertising.
  Health affairs (Project Hope) 2008 Linden A
• Narrow model.
  Health affairs (Project Hope) 2008 Linden A
• Sample size in disease management program evaluation: the challenge of demonstrating a statistically significant reduction in admissions.
  Disease management : DM 2008 Linden A
• Disease management in chronic kidney disease.
  Advances in chronic kidney disease 2008 Rastogi A, Linden A, Nissenson AR
• Medicare disease management in policy context.
  Health care financing review 2008 Linden A, Adler-Milstein J
• The case-mix of chronic illness hospitalization rates in a managed care population: implications for health management programmes.
  Journal of evaluation in clinical practice 2007 Linden A, Goldberg S
• Evaluation of a medicaid asthma disease management program.
  Disease management : DM 2007 Linden A, Berg GD, Wadhwa S
• Determining if disease management saves money: an introduction to meta-analysis.
  Journal of evaluation in clinical practice 2007 Linden A, Adams JL
• A conceptual framework for targeting prediabetes with lifestyle, clinical, and behavioral management interventions.
  Disease management : DM 2007 Biuso TJ, Butterworth S, Linden A
• Consensus development and application of ICD-9 codes for defining chronic illnesses and their complications
  Dis Manage Health Outcomes 2007 Linden A, Biuso TJ, Gopal A, Barker AF, Cigarroa J, Haranath SP, Rinkevich D, Stajduhar K.
• Estimating the effect of regression to the mean in health management programs
  Dis Manage Health Outcomes 2007 Linden A.
• Health coaching as an intervention in health management programs
  Dis Manage Health Outcomes 2007 Butterworth S, Linden A, McClay W.
• Use of the total population approach to measure U.S. disease management industry's cost savings: issues and implications
  Dis Manage Health Outcomes 2007 Linden A.
• Evaluating program effectiveness using the regression point displacement design.
  Evaluation & the health professions 2006 Linden A, Trochim WM, Adams JL
• Effect of motivational interviewing-based health coaching on employees' physical and mental health status.
  Journal of occupational health psychology 2006 Butterworth S, Linden A, McClay W, Leo MC
• Is Israel ready for disease management?
  The Israel Medical Association journal : IMAJ 2006 Linden A
• Disease management interventions II: What else is in the black box?
  Disease management : DM 2006 Linden A, Butterworth SW, Roberts N
• Evaluating disease management programme effectiveness: an introduction to instrumental variables.
  Journal of evaluation in clinical practice 2006 Linden A, Adams JL
• Evaluating disease management programme effectiveness: an introduction to the regression discontinuity design.
  Journal of evaluation in clinical practice 2006 Linden A, Adams JL, Roberts N
• Measuring diagnostic and predictive accuracy in disease management: an introduction to receiver operating characteristic (ROC) analysis.
  Journal of evaluation in clinical practice 2006 Linden A
• Strengthening the case for disease management effectiveness: un-hiding the hidden bias.
  Journal of evaluation in clinical practice 2006 Linden A, Adams JL, Roberts N
• What will it take for disease management to demonstrate a return on investment? New perspectives on an old theme.
  The American journal of managed care 2006 Linden AL
• Evaluating the effectiveness of home health as a disease management strategy
  Home Health Care Management & Practice 2006 Linden A.
• In search of financial savings from disease management: Applying the number needed to decrease (NND) analysis to a diabetic population
  Dis Manage Health Outcomes 2006 Linden A, Biuso TJ.
• Using visual displays as a tool to demonstrate disease management program effectiveness.
  Disease management : DM 2005 Linden A, Roberts N
• Letter regarding article by Galbreath et al, "Long-term healthcare and cost outcomes of disease management in a large, randomized, community-based population with heart failure".
  Circulation 2005 Linden A, Wilson T
• Potential bias in "controls" used in a heart failure disease-management program.
  Journal of the American Geriatrics Society 2005 Wilson T, Linden A
• Financial interests, detailed description of methods, and use of randomized design in a real-world setting.
  The American journal of managed care 2005 Wilson T, Linden A
• Asthma disease management: regression to the mean or better?
  The American journal of managed care 2005 Wilson T, Linden A
• Care management for heart failure.
  Annals of internal medicine 2005 Linden A, Wilson T
• Disease management's economic impact: unproven?
  Health affairs (Project Hope) 2005 Wilson T, Linden A
• A user's guide to the disease management literature: recommendations for reporting and assessing program outcomes.
  The American journal of managed care 2005 Linden A, Roberts N
• Evaluating disease management program effectiveness: An introduction to the bootstrap technique
  Dis Manage Health Outcomes 2005 Linden A, Adams J, Roberts N.
• Using propensity scores to construct comparable control groups for disease management program evaluation
  Dis Manage Health Outcomes 2005 Linden A, Adams J, Roberts N.
• Measuring diabetes management.
  Health affairs (Project Hope) 2004 Wilson T, Linden A
• Generalizing disease management program results: how to get from here to there.
  Managed care interface 2004 Linden A, Adams JL, Roberts N
• Disease management interventions: what's in the black box?
  Disease management : DM 2004 Linden A, Roberts N
• Evaluating disease management program effectiveness adjusting for enrollment (tenure) and seasonality
  Research in Health Financial Management 2004 Linden A, Adams J, Roberts N.
• Evaluating disease management program effectiveness: an introduction to survival analysis.
  Disease management : DM 2004 Linden A, Adams JL, Roberts N
• Using an empirical method for establishing clinical outcome targets in disease management programs.
  Disease management : DM 2004 Linden A, Adams JL, Roberts N
• An assessment of the total population approach for evaluating disease management program effectiveness.
  Disease management : DM 2003 Linden A, Adams JL, Roberts N
• Evaluating disease management program effectiveness: an introduction to time-series analysis.
  Disease management : DM 2003 Linden A, Adams JL, Roberts N
• The complete "how to" guide for selecting a disease management vendor.
  Disease management : DM 2003 Linden A, Roberts N, Keck K
• A Risk Adjusted Method of Analysis for Bed-day Reporting at CareAmerica Health Plans
  A Risk Adjusted Method of Analysis for Bed-day Reporting at CareAmerica Health Plans. 1997 Linden A.
• A physiological comparison of forward vs reverse wheelchair ergometry
  Medicine & Science in Sports & Exercise 1993 Linden A, Holland GJ, Loy SF, Vincent WJ.