Verification and validation of simulation models

Sargent, Robert G.

doi:10.1109/wsc.2009.5429327

Cited by 62 publications

(19 citation statements)

References 43 publications

(36 reference statements)

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“…The limitations of a computational, theoretical method are evident and involve the inherent assumptions of the mathematical model from both a physiologic and an anatomic position. However, the validation comparisons are considered within the reasonable range of error for this type of biologic modeling ( 31 , 32 ). Further, although more accurate results are possible through manipulation of the mathematics of the model’s parameters and structure, this process would not be true to the experimental literature upon which the model was constructed, potentially leading to conclusion with tenuous foundations.…”

Section: Discussionmentioning

confidence: 99%

Theoretical Analysis of the Relative Impact of Obesity on Hemodynamic Stability During Acute Hemorrhagic Shock

et al. 2015

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Background:Evidence suggests that morbid obesity may be an independent risk factor for adverse outcomes in patients with traumatic injuries.Objectives:In this study, a theoretic analysis using a derivation of the Guyton model of cardiovascular physiology examines the expected impact of obesity on hemodynamic changes in Mean Arterial Pressure (MAP) and Cardiac Output (CO) during Hemorrhagic Shock (HS).Patients and Methods:Computer simulation studies were used to predict the relative impact of increasing Body Mass Index (BMI) on global hemodynamic parameters during HS. The analytic procedure involved recreating physiologic conditions associated with changing BMI for a virtual subject in an In Silico environment. The model was validated for the known effect of a BMI of 30 on iliofemoral venous pressures. Then, the relative effect of changing BMI on the outcome of target cardiovascular parameters was examined during simulated acute loss of blood volume in class II hemorrhage. The percent changes in these parameters were compared between the virtual nonobese and obese subjects. Model parameter values are derived from known population distributions, producing simulation outputs that can be used in a deductive systems analysis assessment rather than traditional frequentist statistical methodologies.Results:In hemorrhage simulation, moderate increases in BMI were found to produce greater decreases in MAP and CO compared to the normal subject. During HS, the virtual obese subject had 42% and 44% greater falls in CO and MAP, respectively, compared to the nonobese subject. Systems analysis of the model revealed that an increase in resistance to venous return due to changes in intra-abdominal pressure resulting from obesity was the critical mechanism responsible for the differences.Conclusions:This study suggests that obese patients in HS may have a higher risk of hemodynamic instability compared to their nonobese counterparts primarily due to obesity-induced increases in intra-abdominal pressure resulting in reduced venous return.

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Section: Discussionmentioning

confidence: 99%

Theoretical Analysis of the Relative Impact of Obesity on Hemodynamic Stability During Acute Hemorrhagic Shock

et al. 2015

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“…Metamodeling techniques [29], i.e., modeling the simulation model outputs as functions of simulation inputs, can circumvent getting the simulation results for all variables in the parameter space. These topics are beyond the scope of this report; we suggest reviewing Sargent [30] and Law [31].…”

Section: Model Validationmentioning

confidence: 99%

Application of Constrained Optimization Methods in Health Services Research: Report 2 of the ISPOR Optimization Methods Emerging Good Practices Task Force

et al. 2018

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Constrained optimization methods are informative in providing insights to decision makers about optimal target solutions and the magnitude of the loss of benefit or increased costs associated with the ultimate clinical decision or policy choice. Failing to identify a mathematically superior or optimal solution represents a missed opportunity to improve economic efficiency in the delivery of care and clinical outcomes for patients. The ISPOR Optimization Methods Emerging Good Practices Task Force's first report provided an introduction to constrained optimization methods to solve important clinical and health policy problems. This report also outlined the relationship of constrained optimization methods relative to traditional health economic modeling, graphically illustrated a simple formulation, and identified some of the major variants of constrained optimization models, such as linear programming, dynamic programming, integer programming, and stochastic programming. The second report illustrates the application of constrained optimization methods in health care decision making using three case studies. The studies focus on determining optimal screening and vaccination strategies for cervical cancer, optimal statin start times for diabetes, and an educational case to invite the reader to formulate radiation therapy optimization problems. These illustrate a wide range of problem types that can be addressed with constrained optimization methods.

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“…A clear description of the phenomena to be explained by the model and the testing of the simplest and realistic proxy behavior rules are the key to successful ABM validation [73]. In this regard, Zeigler et al [74] proposed three different types of validity: replicative validity (i.e., the model "matches data already acquired from the real system"), structural validity (i.e., the model "truly reflects the way in which the real system operates") and predictive validity (i.e., the model "matches data before data acquired from the real system"). This paper mainly studies the influence of social groups and social factors on unsafe behaviors, rather than specifically predicting the occurrence of unsafe behaviors.…”

Section: Model Validationmentioning

confidence: 99%

Understanding the Sociocognitive Process of Construction Workers’ Unsafe Behaviors: An Agent-Based Modeling Approach

Yue

Yang

et al. 2020

IJERPH

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Previous literature has recognized that workers' unsafe behavior is the combined result of both isolated individual cognitive processes and their interaction with others. Based on the consideration of both individual cognitive factors and social organizational factors, this paper aims to develop an Agent-Based Modeling (ABM) approach to explore construction workers' sociocognitive processes under the interaction with managers, coworkers, and foremen. The developed model is applied to explore the causes of cognitive failure of construction workers and the influence of social groups and social organizational factors on the workers' unsafe behavior. The results indicate that (1) workers' unsafe behaviors are gradually reduced with the interaction with managers, foremen, and workers; (2) the foreman is most influential in reducing workers' unsafe behaviors, and their demonstration role can hardly be ignored; (3) the failure of sociocognitive process of construction workers is affected by many factors, and cognitive process errors could be corrected under social norms; and (4) among various social organizational factors, social identity has the most obvious effect on reducing workers' unsafe behaviors, and preventive measures are more effective than reactive measures in reducing workers' unsafe behaviors.

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Verification and validation of simulation models

Cited by 62 publications

References 43 publications

Theoretical Analysis of the Relative Impact of Obesity on Hemodynamic Stability During Acute Hemorrhagic Shock

Theoretical Analysis of the Relative Impact of Obesity on Hemodynamic Stability During Acute Hemorrhagic Shock

Application of Constrained Optimization Methods in Health Services Research: Report 2 of the ISPOR Optimization Methods Emerging Good Practices Task Force

Understanding the Sociocognitive Process of Construction Workers’ Unsafe Behaviors: An Agent-Based Modeling Approach

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