I need your helpe PLEASE!
For my research paper, and In order to develop my dataset, i fielded the missing observation with interpolation/extrapolation method. And I need to ensure the quality and behavior of data before starting my analysis. Could you kindly provide more details on the specific steps and methodologies to be employed to ensure the meaningfulness and verifiability of the results, I am particularly interested in understanding:
- The quality assurance measures taken before and after applying interpolation/extrapolation techniques.
-Is there a trend approach to be adopted to reflect developments within the periods for the missing data?
- and if there are any diagnostic tests to be conducted to validate the reliability of the fielded data.
Thank you in advance for your time and consideration.
BEFORE
1. Data verification:
2. Data preprocessing:
3. Model selection:
4. Validation and cross-validation:
5. Sensitivity analysis:
6. Error estimation:
After applying interpolation or extrapolation techniques, additional quality assurance measures can be taken:
1. Result validation
2. Sensitivity analysis
3. Result visualization:
By following these quality assurance measures, the accuracy and reliability of the interpolation or extrapolation results can be improved, ensuring that the derived values are as valid and useful as possible.
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