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In this paper, we propose an empirical log-likelihood estimator for estimating the population mean of a sensitive variable in the presence of an auxiliary variable.
The tuning of a sensitive variable, in the context of estimating the population mean of a sensitive variable, is also introduced through an unsolved exercise.
Sometimes a variable classified as a quasi-identifier in one context is classified as a sensitive variable in another context.
Because mortality is not a sensitive variable in a trauma population, we also studied a composite endpoint that comprised death, MOF, and ARDS, repeating the analysis performed in the original randomized controlled trial (RCT) [ 24, 25].
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In sensitivity analysis, a sensitive variable is detected when changes in its input value result in considerable changes in the outcome [ 46].
The second part of the tool investigates the distribution of model errors for the different classes of a sensitive variable.
Additionally, R. aurora spend little time seasonally in wetlands, so finding a relationship with wetland size may not be a sensitive variable to measure.
We develop a model for the estimation of the variance of sensitive variable in randomized response procedure, when ranked set sampling (RSS) design is used under ranking criteria.
Temperature is considered the most sensitive variable in SCWG processes, with 600 °C serving as an often-cited, optimal target temperature due to associated high conversion [20, 21, 22].
Consequently, pipe thickness was the most sensitive variable in affecting full energy efficiency of the 185.7 keV signature peak with up to 8% variation in efficiency for ±0.5 mm changes in Schedule 40 304L stainless steel piping.
The most sensitive variable in each case is the cost of the preventative strategy, which at a higher value, makes the ICER of standard care and standard care plus temperature monitoring less favorable.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com