Significance of Sensitivity analysis
Sensitivity analysis is a method used across various scientific disciplines, including science, psychiatry, health sciences, and environmental sciences. It assesses how the results of a study or model are affected by changes in input values, assumptions, or parameters. This technique helps determine the robustness and reliability of findings, identify critical factors, and evaluate the impact of uncertainty. It is also employed to optimize models and understand the influence of different variables on outcomes.
Synonyms: Sensitivity assessment, Parameter sensitivity analysis, Uncertainty analysis, Sensitivity testing, Impact analysis, Impact assessment, Risk analysis, Scenario analysis, Variance analysis
The below excerpts are indicatory and do represent direct quotations or translations. It is your responsibility to fact check each reference.
The concept of Sensitivity analysis in scientific sources
Sensitivity analysis assesses how changes in a model's parameters or inputs impact its outcomes. It helps determine model accuracy, robustness, and identify critical factors, ensuring reliable results across various applications and disciplines.
From: Sustainability Journal (MDPI)
(1) This forms the basis of a Very Fast Learning Method for neural networks.[1] (2) Sensitivity analysis is a method used to examine how changes in key parameters, such as electricity prices and subsidy coefficients, affect the project's investment thresholds and optimal investment timing.[2] (3) Sensitivity analysis was performed on the number of selected concrete batching plants and demands to understand their impact.[3]
From: International Journal of Environmental Research and Public Health (MDPI)
(1) A sensitivity analysis was performed to confirm the robustness of the study's findings by re-specifying models and adjusting for additional relevant factors, ensuring the reliability of the results.[4] (2) This type of analysis indicated that particulate matter is more closely linked to cardiovascular effects than NO 2 .[5] (3) Sensitivity analysis was employed to estimate the association between ambient temperatures and YLL for non-accidental disease death, enhancing the robustness of the findings.[6]
From: The Malaysian Journal of Medical Sciences
(1) Sensitivity analysis is a robustness check in statistical evaluation that was notably missing in some lower-quality papers, where the stability of the results under different assumptions is tested.[7] (2) A sensitivity analysis, specifically employing the leave-one-out method, was conducted to check the robustness of the meta-analysis findings by sequentially removing each study to see if the overall effect size remained stable.[8] (3) The sensitivity analysis was conducted to evaluate the effect of variations in input costs on the overall PNC cost, indicating the impact of changes in specific cost categories.[9]
From: South African Journal of HIV Medicine
(1) It is an examination of how the outcomes of a model or analysis change when the assumptions or parameters are varied, providing insights into robustness.[10] (2) It is a method to determine how different values of an independent variable impact a particular dependent variable under a given set of assumptions, to assess the robustness of the findings.[11] (3) An exploration of the effect of broadening the definition of optimal adherence.[12]
From: South African Journal of Physiotherapy
(1) Often the statistical analysis includes this, where the effect on the outcome is explored if you manipulate certain variables such as quality weights, inclusion and exclusion of weaker studies etc.[13]
From: Journal of Public Health in Africa
(1) It was performed to analyze the uncertainty of the results due to the wide variation in drug prices from brand-name to generic drugs, recalculating the cost based on minimum and maximum prices.[14] (2) This is an examination of how changes in referral time affect the risk of death, where increased referral time is associated with increased mortality.[15] (3) This study consists of a process of recalculating outcomes based on removing inputs to help in determining the relative impact of each study on the reported findings, and it was found that no study was particularly influential on the reported findings.[16]
From: Asian Journal of Pharmaceutics
(1) This was used to examine how outliers affected the estimate as a whole.[17] (2) The sensitivity of the network was the main criterion for the selection of ingredient composition that maximally contributes to sensory evaluation when mixing a smoothie.[18] (3) It is a method used to determine the stability of study results by estimating the magnitude of influence factor on a particular amount of research.[19]
From: South African Journal of Psychiatry
(1) This is a statistical method used to assess the accuracy of a screening tool by comparing its results to a gold standard.[20] (2) The results of this showed that quetiapine remains less costly than haloperidol in almost all cases under the baseline and private 1 situation, according to the study.[21]
From: International Journal of Pharmacology
(1) A method used to test the robustness of meta-analysis findings by removing or altering studies, performed for adverse reactions, hemoglobin, serum ferritin, and transferrin in this study.[22] (2) Sensitivity analysis is a statistical method used to evaluate how the results of a study or model change when key assumptions or inputs are varied, helping to assess the robustness of the findings.[23]
From: Religions Journal (MDPI)
(1) An approach involving running alternative analyses to verify if reported results remain consistent, including examining different model structures and indicators.[24]