Efficient Method to Perform Temperature Sensitivity Analysis and Rank Dominant Components in PSpice

I am working on a precision analog circuit and I want to assess temperature sensitivity and identify which components dominate performance variation due to temperature in an efficient and automated way.

My objective is not simply to observe output variation of a specific performance metric versus temperature, but to:

• Quantify the sensitivity of a performance metric (e.g., output current, impedance, or noise) with respect to temperature
• Attribute this variation to individual components (R, L, C, coupling factors, parasitics, etc.)
• Rank components based on their contribution to the overall temperature-induced variation

One approach I considered is to encode temperature effects as equivalent tolerances (i.e., mapping TC-induced drift into % variation) and then perform a standard sensitivity or worst-case analysis. However, this would require maintaining two versions of the circuit (nominal vs “temperature-perturbed”), which is not practical or scalable.

To clarify, I am not referring to a simple global temperature sweep or single-parameter variation. I am looking for a method that enables systematic decomposition of temperature effects across all components.

 Is there a rigorous and efficient workflow in PSpice/Cadence to:

• perform sensitivity analysis with respect to temperature and
• automatically identify and rank the dominant contributors?

Any guidance on built-in features I may miss would be highly appreciated.