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Partial sensitivity analysis involves examining the impact of varying input parameters on the output of a model while holding other parameters constant. By isolating the effect of individual variables, it helps to understand the influence of each parameter on the model's results and identify which factors have the most significant impact. This analysis is valuable in assessing the robustness and reliability of a model's outcomes.

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