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All multivariate regression models were estimated using Stata Version 13 (http://www.stata.com/stata13/), employing the "cluster" option (to account for physicians in the sample affiliated with the same practice) and the "robust" standard error option (to account for other potential departures from homoscedasticity by using the Huber-White robust standard error estimator).
The quantitative interpretation of LightCycler results was assisted by the "fit point method" algorithm with the "minimize error" option (LightCycler software Vers. 3.5; Roche Diagnostics).
The population pharmacokinetic parameters and associated error were then utilized to simulate expected concentrations for the various levels of CVVH in ADAPT V, using the individual simulation with output error option selected.
The str2d command has a bootstrap standard error option and we recommend researchers use this method instead of the default estimate when calculating λ s, particularly when D≥2.
Don't click on options if it's not obvious what they do (especially the "force error" option).
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Therefore, options that potentially reduce both types of errors (option 5 or higher) are more desirable.
The marginal regression models were fitted in STATA [ 12] using the xtgee command with an identity link function (link (iden)) and the robust standard errors option.
When a paper lacks a CI or the relevant standard error, one option is to contact the authors.
The graph of the MCQ results was produced using the error bar option to display the mean and 95% confidence intervals.
The cross-gene error model option of GeneSpring was turned off so that only the true biological replicates were used to estimate variance.
For sequencing error rates (option '-e'), we ran VAS for two error rates: 2%, a common error rate for 100-bp reads, and 0% as an idealized control group so we can factor out base errors as the source of false-positive or false-negative variation discovery.
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