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Withdrawal completion: "Yes" is an optimistic value and "no" is a pessimistic value.
Continuous outcome measures only assessed after 6 months: An optimistic value equals the highest value in the whole sample and a pessimistic value the lowest value, if increasing the outcome measure is considered beneficial.
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For example, a is the pessimistic value, and b is the optimistic value in the interval ((a, b]) or ([a, b]).
In order to model the problem within the framework of the credibility optimization, three types of new defuzzification criteria, i.e., optimistic value criterion, pessimistic value criterion and expected value criterion, are proposed for type-2 fuzzy variables.
To deal quantitatively with imprecision or uncertainty, cash flows are modeled as triangular fuzzy numbers which represent "the most likely possible value", "the most pessimistic value" and "the most optimistic value".
In contrast, one can calculate the most pessimistic value (i.e. smallest possible value) of the mean free path of the air molecules by maximizing the number density (i.e. at maximum operating vacuum pressure and minimum experienced temperature) and assuming the upper range of the reported hard shell diameter for the gas molecules.
Missing values will be replaced by the most pessimistic value in the opposite group.
Missing values will be imputed by most pessimistic value in the group to which it belongs.
Under a worst-case scenario the most pessimistic values (Table 6) predicted disappearance of AA in one generation and of AB in two generations or 10 years (Figure 7 panel 4).
Optimistic and pessimistic values are inferred as follows: Dose after 2, 4, and 6 months: Pessimistic values will be imputed as follows: Data will be reviewed from left to right setting the 2 months value, if it is missing, to equal the baseline value.
As the participants lost to follow-up were excluded from the analyses, a sensitivity analysis on the persistence of KP was performed assuming two extreme scenarios on the missing values: a pessimistic scenario, in which all missing individuals had KP at follow-up and an optimistic scenario, in which no missing individuals had KP at follow-up.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com