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Concept and evaluation of robustness of analytical methods are also discussed.
Finding and checking robustness of analytical methods are two different problems which must be treated with different tools.
Population-based design, large numbers and robustness of analytical procedures are the main strengths.
Population-based design, 30-day outcomes, large numbers and robustness of analytical procedures are the main strengths.
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The two-level full factorial designs would be the most recommended for robustness evaluations of analytical methods.
The robustness of the analytical method to extract drug from microparticles is also assessed.
The robustness of an analytical procedure is a measure of its capacity to remain unaffected by small but deliberate variations made in method parameters.
A procedure to evaluate the robustness of an analytical method when there are changes in some experimental variables, when using multivariate calibration, is proposed.
Robustness of the analytical method was tested using a three-leveled Plackett Burman design in which 11 factors were assessed with 23 experiments.
The robustness of an analytical procedure is a measure of its capacity to remain unaffected by small, but deliberate variations in method parameters and provides an indication of its reliability during normal usage [16].
Given that the results of fuzzy-set qualitative comparative analysis is sensitive to the assignment of fuzzy-set scores (Skaaning 2011), it is necessary to test the robustness of the analytical results.
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