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Uncovering heterogeneous effects in computational models for sustainable decision-making
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Uncovering heterogeneous effects in computational models for sustainable decision-making (2023)Uncovering heterogeneous effects in compu…The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support (2020)The Future of Sensitivity Ana…Five ways to ensure that models serve society: a manifesto (2020)Five ways to ensure that mode…Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices (2019)Why so many published sensiti…Comparison of four heterogeneity measures for meta‐analysis (2019)Comparison of four heterogene…Real option valuation in renewable energy literature: Research focus, trends and design (2017)Real option valuation in rene…Sensitivity analysis of environmental models: A systematic review with practical workflow (2016)Sensitivity analysis of envir…Sensitivity analysis: A review of recent advances (2015)Sensitivity analysis: A revie…A Matlab toolbox for Global Sensitivity Analysis (2015)A Matlab toolbox for Global S…Making sense of global sensitivity analyses (2013)Making sense of global sensit…How small system dynamics models can help the public policy process (2010)How small system dynamics mod…Environmental Cost-Benefit Analysis (2008)Environmental Cost-Benefit An…Global Sensitivity Analysis. The Primer (2007)Global Sensitivity Analysis. …Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models (2005)Sensitivity Analysis in Pract…Quantifying heterogeneity in a meta‐analysis (2002)Quantifying heterogeneity in …Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (2001)Global sensitivity indices fo…Response Surface Methodology: Process and Product Optimization Using Designed Experiments (1996)Response Surface Methodology:…Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I Theory (1973)Factorial Sampling Plans for Preliminary Computational Experiments (1991)Global Sensitivity Analysis of environmental models: Convergence and validation (2016)Most computational hydrology is not reproducible, so is it really science? (2016)The Combination of Estimates from Different Experiments (1954)Meta-analysis in clinical trials (1986)Measuring inconsistency in meta-analyses (2003)The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration (2009)Conducting Meta-Analyses in R with the metafor Package (2010)Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index (2009)Why Most Published Research Findings Are False (2005)Sensitivity analysis methods in the biomedical sciences (2020)Toward SALib 2.0: Advancing the accessibility and interpretability of global sensitivity analyses (2022)Design and Analysis of Computer Experiments (1989)Sensitivity analysis: A discipline coming of age (2021)Enhancing the explainability of regression-based polynomial chaos expansion by Shapley additive explanations (2022)Statistics for Experimenters (1979)Research Issues and Ideas in Statistical Process Control (1999)Modeling and optimization I: Usability of response surface methodology (2006)Response surface methodology (2010)Risk, Ambiguity, and the Savage Axioms (1961)The Price of Robustness (2004)Risk assessment and risk management: Review of recent advances on their foundation (2015)SALib: An open-source Python library for Sensitivity Analysis (2017)Handbook on Constructing Composite Indicators (2005)An effective screening design for sensitivity analysis of large models (2007)Handbook on Constructing Composite Indicators: Methodology and User Guide (2008)A new uncertainty importance measure (2006)
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References

  • 2002Quantifying heterogeneity in a meta‐analysis36,730 cited
  • 2007Global Sensitivity Analysis. The Primer6,425 cited
  • 2001Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates6,377 cited
  • 1996Response Surface Methodology: Process and Product Optimization Using Designed Experiments3,255 cited
  • 2005Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models1,843 cited
  • 2016Sensitivity analysis of environmental models: A systematic review with practical workflow1,722 cited
  • 2015Sensitivity analysis: A review of recent advances1,172 cited
  • 2019Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices827 cited
  • 2015A Matlab toolbox for Global Sensitivity Analysis655 cited
  • 2020The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support632 cited
  • 2020Five ways to ensure that models serve society: a manifesto491 cited
  • 2010How small system dynamics models can help the public policy process420 cited
  • 2013Making sense of global sensitivity analyses231 cited
  • 2008Environmental Cost-Benefit Analysis202 cited
  • 2019Comparison of four heterogeneity measures for meta‐analysis

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186 cited
  • 2017Real option valuation in renewable energy literature: Research focus, trends and design140 cited
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