Sensitivity analysis: Difference between revisions

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[[Category:Scientific modeling]]
[[Category:Scientific modeling]]
[[Category:Mathematical and quantitative methods (economics)]]
[[Category:Mathematical and quantitative methods (economics)]]
== Sensitivity_analysis ==
<gallery>
File:Sensitivity_scheme.jpg|Sensitivity scheme
File:Scatter_plots_for_sensitivity_analysis_bis.jpg|Scatter plots for sensitivity analysis
</gallery>

Latest revision as of 21:10, 23 February 2025

An analysis used to determine how sensitive the results of a study or systematic review are to changes in how it was done.

Purpose of sensitivity analysis[edit]

Sensitivity analyses are used to assess how robust the results are to uncertain decisions or assumptions about the data and the methods that were used.

Types of sensitivity analysis[edit]

There are different ways of sensitivity analysis.

  • In the assessment of heterogeneity it is concerned with the effects of inclusion and exclusion of specific studies.
  • In the use of statistical procedures, sensitivity analysis is the repetition of the analysis using different statistical methods of pooling to assess whether the same results are achieved, and whether the quality of the individual studies and publication bias change the pooled estimates.

Use[edit]

All evaluations are characterized by some degree of uncertainty or ignorance about the future course of events. In a sensitivity analysis, the results of the evaluation are re-worked after systematically substituting high and low values for each of the variables of interest (the discount rate or the expected loss to follow up, for example).

Conclusions[edit]

If the conclusions remain unchanged after the re-analysis, then the results can be said to be robust. If the results are not robust, then sensitivity analysis can show where better information will be most useful.

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Sensitivity_analysis[edit]