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Ariel Linden, DrPH

Title(s)Research Specialist, Medicine
SchoolSchool of Medicine
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    University of California, Los AngelesDrPH1997Health Services

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    Dr. Linden is a health services researcher with expertise in evaluating the effectiveness of health care interventions and policy changes. As a methodologist, he specializes in developing and implementing techniques to maximize causal inference with observational data. His recent interests include the use of machine learning tools for studying causality and predictive modeling. Dr. Linden has published over 100 peer-reviewed papers and has written 35 statistical software packages for Stata.

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    Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Researchers can login to make corrections and additions, or contact us for help.
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    1. Platt KD, Thompson AN, Lin P, Basu T, Linden A, Fendrick AM. Assessment of Self-monitoring of Blood Glucose in Individuals With Type 2 Diabetes Not Using Insulin. JAMA Intern Med. 2019 Feb 01; 179(2):269-272. PMID: 30534950.
      View in: PubMed
    2. Some machine learning algorithms find relationships between variables when none exist -- CTA doesn’t. Optimal Data Analysis. 2019; 8:64-67.
    3. Novometric stepwise CTA analysis discriminating three class Categories using two ordered attributes. Optimal Data Analysis. 2019; 8:68-71.
    4. Linden A, Yarnold PR.Effect of Sample Size on Discovery of Relationships in Random Data by Classification Algorithms. Optimal Data Analysis. 2019; 8:76-80.
    5. 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; 8:84-93.
    6. Linden A, Yarnold PR.Multi-layer perceptron neural net model identifies effect in random data. Optimal Data Analysis. 2019; 8:94-96.
    7. Linden A, Bryant FB, Yarnold PR.Logistic Discriminant Analysis and Structural Equation Modeling Both Identify Effects in Random Data. Optimal Data Analysis. 2019; 8:97-102.
    8. Ryan AM, Kontopantelis E, Linden A, Burgess JF. Now trending: Coping with non-parallel trends in difference-in-differences analysis. Stat Methods Med Res. 2018 Nov 25; 962280218814570. PMID: 30474484.
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    9. Cross DA, Nong P, Harris-Lemak C, Cohen GR, Linden A, Adler-Milstein J. Practice strategies to improve primary care for chronic disease patients under a pay-for-value program. Healthc (Amst). 2019 Mar; 7(1):30-37. PMID: 30197304.
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    10. Linden A. Using randomization tests to assess treatment effects in multiple-group interrupted time series analysis. J Eval Clin Pract. 2019 Feb; 25(1):5-10. PMID: 30003627.
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    11. Linden A, Yarnold PR. Using machine learning to evaluate treatment effects in multiple-group interrupted time series analysis. J Eval Clin Pract. 2018 08; 24(4):740-744. PMID: 29888469.
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    12. Linden A. Using forecast modelling to evaluate treatment effects in single-group interrupted time series analysis. J Eval Clin Pract. 2018 08; 24(4):695-700. PMID: 29749091.
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    13. Linden A. Using group-based trajectory modelling to enhance causal inference in interrupted time series analysis. J Eval Clin Pract. 2018 06; 24(3):502-507. PMID: 29658192.
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    14. Linden A. Using permutation tests to enhance causal inference in interrupted time series analysis. J Eval Clin Pract. 2018 06; 24(3):496-501. PMID: 29460383.
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    15. Linden A. Combining synthetic controls and interrupted time series analysis to improve causal inference in program evaluation. J Eval Clin Pract. 2018 04; 24(2):447-453. PMID: 29356225.
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    16. Linden A, Yarnold PR.The Australian gun buy-back program and the rate of suicide by firearm. Optimal Data Analysis. 2018; 7:28-35.
    17. Linden A, Yarnold PR.Using ODA in the evaluation of randomized controlled trials. Optimal Data Analysis. 2018; 7:46-49.
    18. Linden A, Yarnold PR.Using ODA in the evaluation of randomized controlled trials: application to survival outcomes. Optimal Data Analysis. 2018; 7:50-53.
    19. Linden A, Yarnold PR.Reanalysis of the National Supported Work Experiment Using ODA. Optimal Data Analysis. 2018; 7:54-58.
    20. Linden A, Yarnold PR.Identifying maximum-accuracy cut-points for diagnostic indexes via ODA. Optimal Data Analysis. 2018; 7:59-65.
    21. Linden A, Yarnold PR.Comparative accuracy of a diagnostic index modeled using (optimized) regression vs. novometrics. Optimal Data Analysis. 2018; 7:66-71.
    22. Linden A.Review of “A Course in Item Response Theory and Modeling with Stata” by Raykov and Marcoulides. Stata Journal. 2018; 18:485-488.
    23. Linden A. A matching framework to improve causal inference in interrupted time-series analysis. J Eval Clin Pract. 2018 04; 24(2):408-415. PMID: 29266646.
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    24. Linden A, Yarnold PR. Estimating causal effects for survival (time-to-event) outcomes by combining classification tree analysis and propensity score weighting. J Eval Clin Pract. 2018 04; 24(2):380-387. PMID: 29230910.
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    25. Linden A, Yarnold PR. Identifying causal mechanisms in health care interventions using classification tree analysis. J Eval Clin Pract. 2018 04; 24(2):353-361. PMID: 29105259.
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    26. Kullgren JT, Krupka E, Schachter A, Linden A, Miller J, Acharya Y, Alford J, Duffy R, Adler-Milstein J. Precommitting to choose wisely about low-value services: a stepped wedge cluster randomised trial. BMJ Qual Saf. 2018 05; 27(5):355-364. PMID: 29066616.
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    27. Linden A, Yarnold PR. Minimizing imbalances on patient characteristics between treatment groups in randomized trials using classification tree analysis. J Eval Clin Pract. 2017 Dec; 23(6):1309-1315. PMID: 28675602.
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    28. Linden A, Yarnold PR. Modeling time-to-event (survival) data using classification tree analysis. J Eval Clin Pract. 2017 Dec; 23(6):1299-1308. PMID: 28670833.
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    29. Linden A, Yarnold PR. Using classification tree analysis to generate propensity score weights. J Eval Clin Pract. 2017 Aug; 23(4):703-712. PMID: 28371206.
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    30. Linden A. Improving causal inference with a doubly robust estimator that combines propensity score stratification and weighting. J Eval Clin Pract. 2017 Aug; 23(4):697-702. PMID: 28116816.
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    31. Linden A. A comparison of approaches for stratifying on the propensity score to reduce bias. J Eval Clin Pract. 2017 Aug; 23(4):690-696. PMID: 28074629.
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    32. Linden A.A comprehensive set of post-estimation measures to enrich interrupted time series analysis. Stata Journal. 2017; 17(1):73–88.
    33. Yarnold PR, Linden A.Computing propensity score weights for CTA models involving perfectly predicted endpoints. Optimal Data Analysis. 2017; 6:43-46.
    34. Linden A. Persistent threats to validity in single-group interrupted time series analysis with a cross over design. J Eval Clin Pract. 2017 Apr; 23(2):419-425. PMID: 27804216.
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    35. Linden A. Challenges to validity in single-group interrupted time series analysis. J Eval Clin Pract. 2017 Apr; 23(2):413-418. PMID: 27630090.
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    36. Linden A, Yarnold PR. Combining machine learning and propensity score weighting to estimate causal effects in multivalued treatments. J Eval Clin Pract. 2016 Dec; 22(6):871-881. PMID: 27421786.
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    37. Linden A, Yarnold PR. Combining machine learning and matching techniques to improve causal inference in program evaluation. J Eval Clin Pract. 2016 Dec; 22(6):864-870. PMID: 27353301.
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    38. Linden A, Yarnold PR, Nallamothu BK. Using machine learning to model dose-response relationships. J Eval Clin Pract. 2016 Dec; 22(6):856-863. PMID: 27240883.
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    39. Linden A, Yarnold PR. Using machine learning to identify structural breaks in single-group interrupted time series designs. J Eval Clin Pract. 2016 Dec; 22(6):851-855. PMID: 27091355.
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    40. Linden A, Yarnold PR. Using machine learning to assess covariate balance in matching studies. J Eval Clin Pract. 2016 Dec; 22(6):844-850. PMID: 27004916.
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    41. Linden A, Yarnold PR. Using data mining techniques to characterize participation in observational studies. J Eval Clin Pract. 2016 Dec; 22(6):835-843. PMID: 26805004.
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    42. 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; 5:41-52.
    43. 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; 22:835-838.
    44. Yarnold PR, Linden A.Novometric analysis with ordered class variables: The optimal alternative to linear regression analysis. Optimal Data Analysis. 2016; 22:65-73.
    45. Yarnold PR, Linden A.Theoretical aspects of the D statistic. Optimal Data Analysis. 2016; 22:171-174.
    46. Linden A. Estimating Measurement Error of the Patient Activation Measure for Respondents with Partially Missing Data. Biomed Res Int. 2015; 2015:270168. PMID: 26636096; PMCID: PMC4655275.
    47. Linden A, Uysal SD, Ryan A, Adams JL. Estimating causal effects for multivalued treatments: a comparison of approaches. Stat Med. 2016 Feb 20; 35(4):534-52. PMID: 26482211.
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    48. Linden A.Conducting interrupted time-series analysis for single- and multiple-group comparisons. Stata Journal. 2015; 15(2):480-500.
    49. Linden A. Graphical displays for assessing covariate balance in matching studies. J Eval Clin Pract. 2015 Apr; 21(2):242-7. PMID: 25545944.
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    50. Linden A, Butterworth S. A comprehensive hospital-based intervention to reduce readmissions for chronically ill patients: a randomized controlled trial. Am J Manag Care. 2014 Oct; 20(10):783-92. PMID: 25365681.
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    51. Linden A. Combining propensity score-based stratification and weighting to improve causal inference in the evaluation of health care interventions. J Eval Clin Pract. 2014 Dec; 20(6):1065-71. PMID: 25266868.
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    52. Linden A.Review of “An Introduction to Stata for Health Researchers, Fourth Edition, by Juul and Frydenberg.”. Stata Journal. 2014; 14(3):697-700.
    53. Linden A. Assessing regression to the mean effects in health care initiatives. BMC Med Res Methodol. 2013 Sep 28; 13:119. PMID: 24073634; PMCID: PMC3849564.
    54. Linden A, Samuels SJ. Using balance statistics to determine the optimal number of controls in matching studies. J Eval Clin Pract. 2013 Oct; 19(5):968-75. PMID: 23910956.
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    55. Elissen AM, Adams JL, Spreeuwenberg M, Duimel-Peeters IG, Spreeuwenberg C, Linden A, Vrijhoef HJ. Advancing current approaches to disease management evaluation: capitalizing on heterogeneity to understand what works and for whom. BMC Med Res Methodol. 2013 Mar 14; 13:40. PMID: 23497125; PMCID: PMC3626873.
    56. Linden A, Karlson KB.Using mediation analysis to identify causal mechanisms in disease management interventions. Health Services and Outcomes Research Methodology. 2013; 13:86-108.
    57. Linden A, Samuels SJ. Estimating measurement error when annualizing health care costs. J Eval Clin Pract. 2013 Oct; 19(5):933-7. PMID: 22844978.
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    58. Linden A, Adams JL. Combining the regression discontinuity design and propensity score-based weighting to improve causal inference in program evaluation. J Eval Clin Pract. 2012 Apr; 18(2):317-25. PMID: 22304484.
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    59. Linden A. Identifying spin in health management evaluations. J Eval Clin Pract. 2011 Dec; 17(6):1223-30. PMID: 21210897.
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    60. Couto J, Webster L, Romney M, Leider H, Linden A.Use of an algorithm applied to urine drug screening to assess adherence to a hydrocodone regimen. Journal of Clinical Pharmacology & Therapeutics. 2011; 36(2):200-207.
    61. Linden A, Bonollo M, Fiddes K.A successful hospital-based disease management program to reduce admissions among patients with multiple chronic illnesses. International Journal of Person Centered Medicine. 2011; 4(1):675-682.
    62. Linden A, Adams JL. Applying a propensity score-based weighting model to interrupted time series data: improving causal inference in programme evaluation. J Eval Clin Pract. 2011 Dec; 17(6):1231-8. PMID: 20973870.
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    63. Linden A. Designing a prospective study when randomization is not feasible. Eval Health Prof. 2011 Jun; 34(2):164-80. PMID: 20696741.
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    64. Linden A, Biuso TJ, Butterworth SW. Help patients with chronic kidney disease stave off dialysis. J Fam Pract. 2010 Apr; 59(4):212-9. PMID: 20398579.
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    65. Linden A, Adams JL. Using propensity score-based weighting in the evaluation of health management programme effectiveness. J Eval Clin Pract. 2010 Feb; 16(1):175-9. PMID: 20367829.
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    66. Linden A, Butterworth SW, Prochaska JO. Motivational interviewing-based health coaching as a chronic care intervention. J Eval Clin Pract. 2010 Feb; 16(1):166-74. PMID: 20367828.
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    67. Linden A, Adams JL. Evaluating health management programmes over time: application of propensity score-based weighting to longitudinal data. J Eval Clin Pract. 2010 Feb; 16(1):180-5. PMID: 20367830.
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    68. Couto JE, Webster L, Romney MC, Leider HL, Linden A. Use of an algorithm applied to urine drug screening to assess adherence to an oxycontin regimen. J Opioid Manag. 2009 Nov-Dec; 5(6):359-64. PMID: 20073409.
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    69. Linden A, Adams JL. Improving participant selection in disease management programmes: insights gained from propensity score stratification. J Eval Clin Pract. 2008 Oct; 14(5):914-8. PMID: 19018926.
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    70. Linden A. Disease management: truth in advertising. Health Aff (Millwood). 2008 Sep-Oct; 27(5):1482-3; author reply 1483-4. PMID: 18780941.
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    71. Linden A. Narrow model. Health Aff (Millwood). 2008 May-Jun; 27(3):899-900; author reply 900. PMID: 18474995.
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    72. Linden A. Sample size in disease management program evaluation: the challenge of demonstrating a statistically significant reduction in admissions. Dis Manag. 2008 Apr; 11(2):95-101. PMID: 18393649.
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    73. Rastogi A, Linden A, Nissenson AR. Disease management in chronic kidney disease. Adv Chronic Kidney Dis. 2008 Jan; 15(1):19-28. PMID: 18155106.
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    74. Linden A, Adler-Milstein J. Medicare disease management in policy context. Health Care Financ Rev. 2008; 29(3):1-11. PMID: 18567239; PMCID: PMC4195041.
    75. Linden A, Goldberg S. The case-mix of chronic illness hospitalization rates in a managed care population: implications for health management programmes. J Eval Clin Pract. 2007 Dec; 13(6):947-51. PMID: 18070267.
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    76. Linden A, Berg GD, Wadhwa S. Evaluation of a medicaid asthma disease management program. Dis Manag. 2007 Oct; 10(5):266-72. PMID: 17961079.
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    77. Linden A, Adams JL. Determining if disease management saves money: an introduction to meta-analysis. J Eval Clin Pract. 2007 Jun; 13(3):400-7. PMID: 17518806.
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    78. Biuso TJ, Butterworth S, Linden A. A conceptual framework for targeting prediabetes with lifestyle, clinical, and behavioral management interventions. Dis Manag. 2007 Feb; 10(1):6-15. PMID: 17309360.
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    79. Linden A.Estimating the effect of regression to the mean in health management programs. Dis Manage Health Outcomes. 2007; 15(1):7-12.
    80. Linden A.Use of the total population approach to measure U.S. disease management industry's cost savings: issues and implications. Dis Manage Health Outcomes. 2007; 15(1):13-18.
    81. Butterworth S, Linden A, McClay W.Health coaching as an intervention in health management programs. Dis Manage Health Outcomes. 2007; 15(5):299-307.
    82. Linden A, Biuso TJ, Gopal A, Barker AF, Cigarroa J, Haranath SP, Rinkevich D, Stajduhar K.Consensus development and application of ICD-9 codes for defining chronic illnesses and their complications. Dis Manage Health Outcomes. 2007; 15(5):315-322.
    83. Linden A, Trochim WM, Adams JL. Evaluating program effectiveness using the regression point displacement design. Eval Health Prof. 2006 Dec; 29(4):407-23. PMID: 17102063.
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    84. Linden A. Is Israel ready for disease management? Isr Med Assoc J. 2006 Oct; 8(10):667-71. PMID: 17125109.
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    85. Butterworth S, Linden A, McClay W, Leo MC. Effect of motivational interviewing-based health coaching on employees' physical and mental health status. J Occup Health Psychol. 2006 Oct; 11(4):358-65. PMID: 17059299.
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    86. Linden A, Adams JL, Roberts N. Strengthening the case for disease management effectiveness: un-hiding the hidden bias. J Eval Clin Pract. 2006 Apr; 12(2):140-7. PMID: 16579822.
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    87. Linden A, Adams JL. Evaluating disease management programme effectiveness: an introduction to instrumental variables. J Eval Clin Pract. 2006 Apr; 12(2):148-54. PMID: 16579823.
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    88. Linden AL. What will it take for disease management to demonstrate a return on investment? New perspectives on an old theme. Am J Manag Care. 2006 Apr; 12(4):217-22. PMID: 16610923.
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    89. Linden A, Adams JL, Roberts N. Evaluating disease management programme effectiveness: an introduction to the regression discontinuity design. J Eval Clin Pract. 2006 Apr; 12(2):124-31. PMID: 16579820.
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    90. Linden A, Butterworth SW, Roberts N. Disease management interventions II: What else is in the black box? Dis Manag. 2006 Apr; 9(2):73-85. PMID: 16620193.
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    91. Linden A. Measuring diagnostic and predictive accuracy in disease management: an introduction to receiver operating characteristic (ROC) analysis. J Eval Clin Pract. 2006 Apr; 12(2):132-9. PMID: 16579821.
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    92. Linden A.Evaluating the effectiveness of home health as a disease management strategy. Home Health Care Management & Practice. 2006; 3(18):216-222.
    93. Linden A, Biuso TJ.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; 4(14):197-202.
    94. Linden A, Roberts N. Using visual displays as a tool to demonstrate disease management program effectiveness. Dis Manag. 2005 Oct; 8(5):301-10. PMID: 16212515.
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    95. Linden A, Wilson T. 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 Jul 05; 112(1):e11; author reply e11. PMID: 15998687.
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    96. Wilson T, Linden A. Potential bias in "controls" used in a heart failure disease-management program. J Am Geriatr Soc. 2005 Jul; 53(7):1268-9. PMID: 16108960.
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    97. Wilson T, Linden A. Financial interests, detailed description of methods, and use of randomized design in a real-world setting. Am J Manag Care. 2005 Jun; 11(6):384; author reply 394. PMID: 15974557.
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    98. Wilson T, Linden A. Disease management's economic impact: unproven? Health Aff (Millwood). 2005 Mar-Apr; 24(2):566-7; author reply 567. PMID: 15757944.
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    99. Linden A, Wilson T. Care management for heart failure. Ann Intern Med. 2005 Mar 01; 142(5):386; author reply 386. PMID: 15738460.
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    100. Wilson T, Linden A. Asthma disease management: regression to the mean or better? Am J Manag Care. 2005 Mar; 11(3):136; author reply 136-7. PMID: 15786850.
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    101. Linden A, Roberts N. A user's guide to the disease management literature: recommendations for reporting and assessing program outcomes. Am J Manag Care. 2005 Feb; 11(2):113-20. PMID: 15726859.
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    102. Linden A, Adams J, Roberts N.Using propensity scores to construct comparable control groups for disease management program evaluation. Dis Manage Health Outcomes. 2005; 13(2):107-127.
    103. Linden A, Adams J, Roberts N.Evaluating disease management program effectiveness: An introduction to the bootstrap technique. Dis Manage Health Outcomes. 2005; 3(13):159-167.
    104. Wilson T, Linden A. Measuring diabetes management. Health Aff (Millwood). 2004 Nov-Dec; 23(6):277-8; author reply 278-9. PMID: 15537618.
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    105. Linden A, Adams JL, Roberts N. Generalizing disease management program results: how to get from here to there. Manag Care Interface. 2004 Jul; 17(7):38-45. PMID: 15341247.
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    106. Linden A, Adams JL, Roberts N. Evaluating disease management program effectiveness: an introduction to survival analysis. Dis Manag. 2004; 7(3):180-90. PMID: 15669578.
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    107. Linden A, Adams JL, Roberts N. Using an empirical method for establishing clinical outcome targets in disease management programs. Dis Manag. 2004; 7(2):93-101. PMID: 15228794.
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    108. Linden A, Roberts N. Disease management interventions: what's in the black box? Dis Manag. 2004; 7(4):275-91. PMID: 15671785.
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    109. Linden A, Adams J, Roberts N.Evaluating disease management program effectiveness adjusting for enrollment (tenure) and seasonality. Research in Health Financial Management. 2004; 9(1):57-68.
    110. Linden A, Adams JL, Roberts N. Evaluating disease management program effectiveness: an introduction to time-series analysis. Dis Manag. 2003; 6(4):243-55. PMID: 14736348.
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    111. Linden A, Roberts N, Keck K. The complete "how to" guide for selecting a disease management vendor. Dis Manag. 2003; 6(1):21-6. PMID: 12899564.
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    112. Linden A, Adams JL, Roberts N. An assessment of the total population approach for evaluating disease management program effectiveness. Dis Manag. 2003; 6(2):93-102. PMID: 14577903.
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    113. Linden A.A Risk Adjusted Method of Analysis for Bed-day Reporting at CareAmerica Health Plans. 1997.
    114. Linden A, Holland GJ, Loy SF, Vincent WJ.A physiological comparison of forward vs reverse wheelchair ergometry. Medicine & Science in Sports & Exercise. 1993; 11(25):1265-1268.