Linden Consulting Group logo  
Linden Consulting Group
Home
About us
Publications
Statistical Software
Upcoming Events
Links
Clients
Contact us

With over 25 years of experience in medical - healthcare research and management, we can help you design, implement, and evaluate

  • Medical management, disease management and health promotion programs
  • Medical home model, accountable care organizations
  • Clinical quality improvement initiatives, operational processes
  • Government, accreditation, and contractual requirements
  • Financial planning and measurement
  • Most any other needs of today’s healthcare market

Awards and Recognition

  • "Leader in Disease Management" by Managed Healthcare Executive
  • "Outstanding Journal Article" Award by Disease Management Association of America
  • "Best of Business" by the Small Business Commerce Association
Highlighted Publication
Linden A. Using Randomization tests to assess treatment effects in multiple-group interrupted time series analysis. Journal of Evaluation in Clinical Practice DOI: 10.1111/jep.12995

Linden A, Yarnold PR. Using machine learning to evaluate treatment effects in multiple-group interrupted time series analysis. Journal of Evaluation in Clinical Practice DOI: 10.1111/jep.12966

Linden A. Using forecast modelling to evaluate treatment effects in single-group interrupted time series analysis. Journal of Evaluation in Clinical Practice DOI: 10.1111/jep.12946

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 randomized trial. BMJ – Quality & Safety DOI: 10.1136/bmjqs-2017-006699
Linden A. Review of “A Course in Item Response Theory and Modeling with Stata” by Raykov and Marcoulides. Stata Journal 2018;18:485-488.
Linden A. Using group-based trajectory modelling to enhance causal inference in interrupted time series analysis. Journal of Evaluation in Clinical Practice 2018;24:502-507.
Linden A. Using permutation tests to enhance causal inference in interrupted time series analysis. Journal of Evaluation in Clinical Practice 2018;24:496-501.

Linden A. Combining synthetic controls and interrupted time series analysis to improve causal inference in program evaluation. Journal of Evaluation in Clinical Practice 2018;24:447-453.

Linden A. A matching framework to improve causal inference in interrupted time series analysis. Journal of Evaluation in Clinical Practice 2018;24:408-415.
Linden A, Yarnold PR. Estimating causal effects for survival (time-to-event) outcomes by combining classification tree analysis and propensity score weighting. Journal of Evaluation in Clinical Practice 2018;24:380-387.
Linden A, Yarnold PR. Identifying causal mechanisms in health care interventions using classification tree analysis. Journal of Evaluation in Clinical Practice 2018;24:353-361.
designed by: Homer Gaines
© 2003-2018 Linden Consulting Group, LLC