Publications using Analytica
Hundreds of journal articles and other publications are based on research using Analytica. We list some of these below, with links to the original articles where available.
Read publications from a wide variety of areas:
M.G. Morgan and M. Henrion, Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis, 2nd edition, Cambridge UP, New York, 1990. See chapter 10: Analytica: A Software Tool for Uncertainty Analysis and Model Communication.
Jorge E. Muro Arbulú, “Toma de decisiones bajo incertidumbre: Enfoque estadístico. Uso de simulaciones para la mejora de las decisiones”, 2019, ISBN 978-612-00-4440-7. pp 594. (Title translation: Decision making under uncertainty: A statistical approach. Use of simulations to improve decisions.) See our review.
Mark E. Borsuk, Peter Reichert, Armin Peter, Eva Schager and Patricia Burkhardt-Holm (Feb 2006), Assessing the decline of brown trout (Salmo trutta) in Swiss rivers using a Bayesian probability network, Ecological Modelling 192(1-2):224-244.
Mark E. Borsuk, , Craig A. Stow1 and Kenneth H. Reckhow (Apr 2004), A Bayesian network of eutrophication models for synthesis, prediction, and uncertainty analysis, Ecological Modelling 173(2-3):219-239.
Mark E. Borsuk, Sean P. Powers, and Charles H. Peterson (2002), A survival model of the effects of bottom-water hypoxia on the population density of an estuarine clam (Macoma balthica), Canadian Journal of Fisheries and Aquatic Sciences (59):1266-1274.
Rebecca Montville and Donald Schaffner (Feb 2005), Monte Carlo Simulation of Pathogen Behavior during the Sprout Production Process, Applied and Environmental Microbiology 71(2):746-753.
S. K. J. Rasmussen, T. Ross, J. Olley and T. McMeekin (2002), A process risk model for the shelf life of Atlantic salmon fillets, International Journal of Food Microbiology 73(1):47-60.
Emissions Policy Analysis
C. Bloyd, J. Camp, G. Conzelmann, J. Formento, J. Molburg, J. Shannon, M. Henrion, R. Sonnenblick, K. Soo Hoo, J. Kalagnanam, S. Siegel, R. Sinha, M. Small, T. Sullivan, R. Marnicio, P. Ryan, R. Turner, D. Austin, D. Burtraw, D. Farrell, T. Green, A. Krupnick, and E. Mansur (Dec 1996), Tracking and Analysis Framework (TAF) Model Documentation and User’s Guide: An Interaction Model for Integrated Assessment of Title IV of the Clean Air Act Amendments, Decision and Information Sciences Division, Argonne National Laboratory.
Max Henrion, Richard Sonnenblick, Cary Bloyd (Jan 1997), Innovations in Integrated Assessment: The Tracking and Analysis Framework (TAF), Air and Waste Management Conference on Acid Rain and Electric Utilities, Scottsdale, AZ.
Richard Sonnenblick and Max Henrion (Jan 1997), Uncertainty in the Tracking and Analysis Framework Integrated Assessment: The Value of Knowing How Little You Know, Air and Waste Management Conference on Acid Rain and Electric Utilities, Scottsdale, Arizona.
R. Sinha, M. J. Small, P. F. Ryan, T. J. Sullivan and B. J. Cosby (July 1998),Reduced-Form Modelling of Surface Water and Soil Chemistry for the Tracking and Analysis Framework, Water, Air, & Soil Pollution 105(3-4).
Dallas Burtraw and Erin Mansur (Mar 1999), The Effects of Trading and Banking in the SO2 Allowance Market, Discussion paper 99-25, Resources for the Future.
Galen mcKinley, Miriam Zuk, Morten Höjer, Montserrat Avalos, Isabel González, Rodolfo Iniestra, Israel Laguna, Miguel A. Martínez, Patricia Osnaya, Luz M. Reynales, Raydel Valdés, and Julia Martínez (2005), Quantification of Local and Global Benefits from Air Pollution Control in Mexico City, Environ. Sci. Technol. 39:1954-1961.
Luis A. CIFUENTES, Enzo SAUMA, Hector JORQUERA and Felipe SOTO (2000), PRELIMINARY ESTIMATION OF THE POTENTIAL ANCILLARY BENEFITS FOR CHILE, Ancillary Benefits and Costs of Greenhouse Gas Mitigation.
Marko Tainio, Jouni T Tuomisto, Otto Hänninen, Juhani Ruuskanen, Matti J Jantunen, and Juha Pekkanen (2007), Parameter and model uncertainty in a life-table model for fine particles (PM2.5): a statistical modeling study, Environ Health 6(24).
L. Basson and J.G. Petrie (Feb 2007), An integrated approach for the consideration of uncertainty in decision making supported by Life Cycle Assessment, Environmental Modeling & Software 22(2):167-176, Environmental Decision Support Systems, Elsevier.
Evan D. Sherwin, Max Henrion, Inês M. L. Azevedo (2018) Estimation of the year-on-year volatility and the unpredictability of the United States energy system, Nature Energy 3:341-346.
Ye Li and H. Keith Florig (Sept. 2006), Modeling the Operation and Maintenance Costs of a Large Scale Tidal Current Turbine Farm, Oceans (2006):1-6.
L.F.Miller, Brian Thomas, J.McConn, J. Hou, J.Preston, T.Anderson, and M.Humberstone (2007), Uncertainty Analysis Methods for Equilibrium Fuel Cycles, ANS Summer Abstract.
Gregory A. Norris and Peter Yost (Fall 2001), Journal of Industrial Ecology 5(4):15-28, MIT Press Journals.
Dallas Burtraw, Karen Palmer, Anthony Paul (Oct 1998), The Welfare Impacts of Restructuring and Environmental Regulatory Reform in the Electric Power Sector, Resources for the Future, presented at Southern Economics Association Meetings, Nov 8-10, 1998 Baltimore, Maryland.
Jouni T Tuomisto and Marko Tainio (2005), An economic way of reducing health, environmental, and other pressures of urban traffic: a decision analysis on trip aggregation, BMC Public Health 5:123. doi:10.1186/1471-2458-5-123.
Yurika Nishioka, Jonathan I. Levy, Gregory A. Norris, Andrew Wilson, Patrick Hofstetter, John D. Spengler (Oct 2002), Integrating Risk Assessment and Life Cycle Assessment: A Case Study of Insulation, Risk Analysis 22(5):1003-1017.
Li, F. G. N. (2017). “Actors behaving badly: Exploring the modeling of non-optimal behavior in energy transitions.” Energy Strategy Reviews 15: 57-71.
Li, F. G. N. and N. Strachan (2019). “Take me to your leader: Using socio-technical energy transitions (STET) modeling to explore the role of actors in decarbonization pathways.” Energy Research & Social Science 51: 67-81.
Henrion, M. (2015). From Controversy to Consensus: A decision analysis for decomissioning California’s offshore oil platforms. ORMS Today 42(1): 22-27.
David G. Groves and Robert J. Lempert (Feb 2007), A new analytic method for finding policy-relevant scenarios, Global Environmental Change 17(1):73-85.
Maged Senbel, Timothy McDaniels, and Hadi Dowlatabadi (July 2003), The ecological footprint: a non-monetary metric of human consumption applied to North America, Global Environmental Change 13(2):83-100.
Dowlatabadi, H. (1998). Sensitivity of Climate Change Mitigation Estimates to Assumptions About Technical Change. Energy Economics 20: 473-93.
West, J. J. and H. Dowlatabadi (1998). On assessing the economic impacts of sea level rise on developed coasts. Climate, change and risk. London, Routledge. 205-20.
Leiss, W., H. Dowlatabadi, and Greg Paoli (2001). Who’s Afraid of Climate Change? A guide for the perplexed. Isuma 2(4): 95-103.
Morgan, M. G., M. Kandlikar, J. Risbey and H. Dowlatabadi (1999). Why conventional tools for policy analysis are often inadequate for problems of global change. Climatic Change 41: 271-81.
Casman, E. A., M. G. Morgan and H. Dowlatabadi (1999). Mixed Levels of Uncertainty in Complex Policy Models. Risk Analysis 19(1): 33-42.
Dowlatabadi, H. (2003). Scale and Scope In Integrated Assessment: lessons from ten years with ICAM. Scaling in Integrated Assessment. J. Rotmans and D. S. Rothman. Lisse, Swetz & Zeitlinger: 55-72.
Dowlatabadi, H. (2000). Bumping against a gas ceiling. Climatic Change 46(3): 391-407.
Morgan, M. G. and H. Dowlatabadi (1996). Learning From Integrated Assessment of Climate Change. Climatic Change 34: 337-368.
Low-Carbon Development: Opportunities for Nigeria, Editors: Raffaello Cervigni, John Allen Rogers, and Max Henrion, No 15812 in World Bank Publications, January 2013. 186p.
Siobain Duffy and Donald W. Schaffner (2001), Modeling the Survival of Escherichia coli O157:H7 in Apply Cider Using Probability Distribution Functions for Quantitative Risk Assessment, Journal of Food Protection 64(5):599-605.
T. A. McMeekin (Sept 2007), Predictive microbiology: Quantitative science delivering quantifiable benefits to the meat industry and other food industries, Meat Science 77(1):17-27.
Y Chen, WH Ross, VN Scott, DE Gombas (2003), Listeria monocytogenes: Low Levels Equal Low Risk, Journal of Food Protection 66(4):570-577(8), International Association for Food Protection.
John Bowers, Anders Dalsgaard, Angelo DePaola, I. Karunasagar, Thomas McMeekin, Mitsuaki, Nishibuchi, Ken Osaka, John Sumner, Mark Walderhaug (2005), Risk assessment of Vibrio vulnificus in raw oysters, World Health Organization: Microbiological Risk Assessment Series (8), 135 pages.
Robert F. Bordley (2014), Reference Class Forecasting: Resolving Its Challenge to Statistical Modeling, The American Statistitcian, 68:4, 221-229, DOI: 10.1080/00031305.2014.937544
Health and Epidemiology
Igor Linkov, Richard Wilson and George M., Gray (1998), Anticarcinogenic Responses in Rodent Cancer Bioassays Are Not Explained by Random Effects, Toxicological Sciences 43(1), Oxford University Press.
M. Loane and R. Wootton (Oct 2001), A simulation model for analysing patient activity in dermatology, Journal of Telemedicine and Telecare 7(1):23-25(3), Royal Society of Medicine Press.
Davis Bu, Eric Pan, Janice Walker, Julia Adler-Milstein, David Kendrick, Julie M. Hook, Caitlin M. Cusack, David W. Bates, and Blackford Middleton (2007), Benefits of Information Technology–Enabled Diabetes Management, Diabetes Care 30:1137-1142, American Diabetes Associaton.
Julia Adler-Milstein, Davis Bu, Eric Pan, Janice Walker, David Kendrick, Julie M. Hook, David W. Bates, Blackford Middleton. The Cost of Information Technology-Enabled Diabetes Management, Disease Management. June 1, 2007, 10(3): 115-128. doi:10.1089/dis.2007.103640.
E. Ekaette, R.C. Lee, K-L Kelly, P. Dunscombe (Aug 2006), A Monte Carlo simulation approach to the characterization of uncertainties in cancer staging and radiation treatment decisions, Journal of the Operational Research Society 58:177-185.
Negar Elmieh, Hadi Dowlatabadi, Liz Casman (Jan 2006), A model for Probabilistic Assessment of Malathion Spray Exposures (PAMSE) in British Columbia, CMU EEP.
Natural Resource Management
S. Schweizer, M.E. Borsuk and P. Reichert (2004), Predicting the Hydraulic and Morphological Consequences of River Rehabilitation, Swiss Frederal Institute for Environmental Science and Technology (EAWAG), International Environmental Modelling and Software Society Transactions.
S. Spörri, M. Borsuk, I. Peters, and P. Reichert (Apr 2007), The economic impacts of river rehabilitation: A regional Input–Output analysis, Ecological Economics 62(2): 341-351.
ME Borsuk, CA Stow, KH Reckhow (2003), An integrated approach to TMDL development for the Neuse River estuary using a Bayesian probability network model (Neu-BERN), Journal of Water Resources Planning and Management.
David G. Groves, Scott Matyac, Tom Hawkins (Apr 2005), QUANTIFIED SCENARIOS OF 2030 CALIFORNIA WATER DEMAND: 2005 California Water Plan Update, Volume 4.
Risk Analysis and Management
Wildlife and Forest Management
Peter B. Woodbury, James E. Smith, David A. Weinstein and John A. Laurence (Aug 1998), Assessing potential climate change effects on loblolly pine growth: A probabilistic regional modeling approach, Forest Ecology and Management 107(1-3), 99-116.
P.R. Richard, M. Power, M. Hammilton (2003), Eastern Hudson Bay Beluga Precautionary Approach Case Study: Risk analysis models for co-management, Canadian Science Advisory Secretariat Research Document.
P.R. Richard (2003), Incorporating Uncertainty in Population Assessments, Canadian Science Advisory Secretariat Research Document.