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Journal of Evaluation in Clinical Practice
|
June 30, 2016
Combining machine learning and matching techniques to improve causal inference in program evaluation
Ariel Linden, Paul R Yarnold
Journal of Evaluation in Clinical Practice
|
August 6, 2013
Using balance statistics to determine the optimal number of controls in matching studies
Ariel Linden, Steven J Samuels
Journal of Evaluation in Clinical Practice
|
April 4, 2017
Using classification tree analysis to generate propensity score weights
Ariel Linden, Paul R Yarnold
Journal of Evaluation in Clinical Practice
|
October 27, 2010
Applying a propensity score-based weighting model to interrupted time series data: improving causal inference in programme evaluation
Ariel Linden, John L Adams
Journal of Evaluation in Clinical Practice
|
November 7, 2017
Identifying causal mechanisms in health care interventions using classification tree analysis
Ariel Linden, Paul R Yarnold
Journal of Evaluation in Clinical Practice
|
April 20, 2016
Using machine learning to identify structural breaks in single-group interrupted time series designs
Ariel Linden, Paul R Yarnold
Journal of Evaluation in Clinical Practice
|
November 21, 2008
Improving participant selection in disease management programmes: insights gained from propensity score stratification
Ariel Linden, John L Adams
Journal of Evaluation in Clinical Practice
|
August 1, 2012
Estimating measurement error when annualizing health care costs
Ariel Linden, Steven J Samuels
Disease Management : DM
|
August 6, 2003
The complete "how to" guide for selecting a disease management vendor
Ariel Linden, Nancy Roberts, Kevin Keck
Disease Management : DM
|
January 23, 2004
Evaluating disease management program effectiveness: an introduction to time-series analysis
Ariel Linden, John L Adams, Nancy Roberts
Page
of 9
Search research articles
Search
Showing results (51-60 of 89) with videos related to
Sort By:
Page
of 9
Journal of Evaluation in Clinical Practice
|
June 30, 2016
Combining machine learning and matching techniques to improve causal inference in program evaluation
Ariel Linden, Paul R Yarnold
Journal of Evaluation in Clinical Practice
|
August 6, 2013
Using balance statistics to determine the optimal number of controls in matching studies
Ariel Linden, Steven J Samuels
Journal of Evaluation in Clinical Practice
|
April 4, 2017
Using classification tree analysis to generate propensity score weights
Ariel Linden, Paul R Yarnold
Journal of Evaluation in Clinical Practice
|
October 27, 2010
Applying a propensity score-based weighting model to interrupted time series data: improving causal inference in programme evaluation
Ariel Linden, John L Adams
Journal of Evaluation in Clinical Practice
|
November 7, 2017
Identifying causal mechanisms in health care interventions using classification tree analysis
Ariel Linden, Paul R Yarnold
Journal of Evaluation in Clinical Practice
|
April 20, 2016
Using machine learning to identify structural breaks in single-group interrupted time series designs
Ariel Linden, Paul R Yarnold
Journal of Evaluation in Clinical Practice
|
November 21, 2008
Improving participant selection in disease management programmes: insights gained from propensity score stratification
Ariel Linden, John L Adams
Journal of Evaluation in Clinical Practice
|
August 1, 2012
Estimating measurement error when annualizing health care costs
Ariel Linden, Steven J Samuels
Disease Management : DM
|
August 6, 2003
The complete "how to" guide for selecting a disease management vendor
Ariel Linden, Nancy Roberts, Kevin Keck
Disease Management : DM
|
January 23, 2004
Evaluating disease management program effectiveness: an introduction to time-series analysis
Ariel Linden, John L Adams, Nancy Roberts
Page
of 9