sensitivity analysis

Sensitivity analysis is a way to deal with these uncertainties.

Sensitivity analysis is an important tool in the study of nuclear systems.

Sensitivity Analysis is common in many areas of physics and chemistry.

Sensitivity analysis can also be used in model-based policy assessment studies.

That is, a sensitivity analysis may shed light into issues not anticipated at the beginning of a study.

A sensitivity analysis can be done to see how much that distribution changes if we change one of our inputs.

We do, however, present a quantitative sensitivity analysis of this assumption in the results section.

Table 4-6 presents the results of this sensitivity analysis.

We used sensitivity analyses to illustrate the potential impact of a different true percentage.

Such number is very efficient compared to more demanding methods for sensitivity analysis.

Sometimes a sensitivity analysis may reveal surprising insights about the subject of interest.

A sensitivity analysis asks questions like, "if we are wrong about a certain input, how much does our best estimate change?"

Sensitivity analysis is actually the best way to analyze data in the presence of dropouts.

The special methods of sensitivity analysis are only used in the former step so we shall concentrate on that.

Ideally, uncertainty and sensitivity analysis should be run in tandem.

Computational expense is a problem in many practical sensitivity analyses.

However there are also some problems associated with sensitivity analysis in the business context:

Again, the general way forward is sensitivity analysis.

From this perspective, info-gap can be seen as a technique of sensitivity analysis, though by no means the only.

Some examples of sensitivity analyses performed in various disciplines follow here.

Our sensitivity analysis showed that the worst and best case imputations were too extreme.

The analysis did not change when we excluded this trial in the sensitivity analysis.

Sensitivity analysis can be useful for a range of purposes, including:

In addition, a sensitivity analysis indicated that the overall treatment effect might be overestimated.

Exhibits 15 and 16 present the results of these sensitivity analyses for 2010 and 2020, respectively.