How to Decide on Modeling Details: Risk and Benefit Assessment

2017 ◽  
pp. 153-193 ◽  
Author(s):  
Mustafa Özilgen
Keyword(s):  
Benefit Assessment ◽  
Risk And Benefit

A risk and benefit assessment for visual-only meat inspection of indoor and outdoor pigs in the United Kingdom

Food Control ◽  
2013 ◽  
Vol 30 (1) ◽  
pp. 255-264 ◽  
Author(s):  
Andrew Hill ◽  
Adam Brouwer ◽  
Neil Donaldson ◽  
Sarah Lambton ◽  
Sava Buncic ◽  
...  
Keyword(s):  
United Kingdom ◽  
Meat Inspection ◽  
Benefit Assessment ◽  
The United Kingdom ◽  
Risk And Benefit ◽  
Indoor And Outdoor

A Risk and Benefit Assessment of Treatment for AIDS-Related Kaposi??s Sarcoma

Drug Safety ◽  
1999 ◽  
Vol 20 (5) ◽  
pp. 403-425 ◽  
Author(s):  
Guglielmo Nasti ◽  
Domenico Errante ◽  
Sandra Santarossa ◽  
Emmanuela Vaccher ◽  
Umberto Tirelli
Keyword(s):  
Benefit Assessment ◽  
Risk And Benefit

Risk and Benefit Assessment of Potential Neurodevelopmental Effect Resulting from Consumption of Marine Fish from a Coastal Archipelago in China

2014 ◽  
Vol 62 (22) ◽  
pp. 5207-5213 ◽  
Author(s):  
Yi-Xiong Gao ◽  
Hongxia Zhang ◽  
Xinwei Yu ◽  
Jia-lu He ◽  
Xiaohong Shang ◽  
...  
Keyword(s):  
Marine Fish ◽  
Benefit Assessment ◽  
Risk And Benefit

Toward an integrated analysis of risk and benefit in clinical research

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 16012-16012
Author(s):  
S. Hirschfeld
Keyword(s):  
Dimensional Space ◽  
Region Of Interest ◽  
Two Dimensions ◽  
Benefit Assessment ◽  
Integrated Analysis ◽  
Time Space ◽  
Integrated Risk ◽  
Risk Benefit Assessment ◽  
Composite Risk ◽  
Risk And Benefit

16012 Background: Clincial data collection can be resource intensive, and yet typically only a proportion of the data is informative to determine outcome. Outcomes are conventionally displayed as single entities or as a composite of several variables for benefit and as single entities, often categorized with regard to severity, for risk. Analysis is then collapsed to a series of analyses expressed in one or two dimensions with several probability factors, one associated with each outcome. Integrated risk-benefit assessment is generally left with individual practitioners to determine, both in consultation with patients and with colleagues as part of a formal or informal consensus process. Methods: A graphical approach assigning each variable of interest plus time a dimension in an n-dimensional space is proposed, calculating the coordinates of each patient as time progresses in that space to describe a path, and describing the sum of all paths for a patient population as bounded by a space. Results: Dispersion of outcomes can be readily determined as well as an integrated risk-benefit index using linear algebra. Comparisons between patient populations can be made on the basis of the boundaries of the space, the dispersion, the vector paths, and the average coordinates at the time of interest of the population as a whole. The number of dimensions can be restricted or expanded as required and can be collapsed into composite risk, including cost, and benefit indices to describe an integrated risk-benefit assessment. A density map can be plotted for all patients in the study space and probabilities assigned for the likelihood of any patient passing through a region of interest. Particular regions within the time-space continuum are then defined as desirable, acceptable, or unacceptable with regard to integrated outcome. Examples will be provided to illustrate the general method. Conclusions: A multidimensional graphical system has been developed to provide an integrated outcome assessment. Multiple analyses are possible including projections, density maps and transformations that may yield further insights into outcomes. Comparisons may be possible using conventional techniques, but in addition new types of comparisons using transformations and other techniques applicable to a space-time continuum may apply. No significant financial relationships to disclose.

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