Your English writing platform
Discover LudwigSuggestions(1)
Similar(60)
The authors propose a procedure, labeled the calibrated sigma method, which is designed to correct for between-group differences in endorsement likelihood of response categories that are unrelated to the content of the items.
All volumes were then spatially realigned [30] to the first volume of the first session to correct for between-scan motion and unwarped [31], and a mean-image from the realigned volumes was created.
Thereby, a minimum of three nurses per department and a maximum of three processes a day for each administrating nurse were observed, to correct for between-person variation.
For each participant, the numbers of statements per coding category were transformed to percentages in order to correct for between-subject variance in verbosity and elaboration of answers.
The 20 trios plus 4 EKs were re-normalised together including a between-array normalisation using wateRmelon package Dasen to correct for between-array effects [ 35].
The mirVana miRNA Reference Panel (Ambion, Austin, TX, USA) was included in each PCR plate in a 2,000-fold 2,000-foldo correct for between-plate dilutionces.
Between-group differences in the use of task-specific schemas were estimated by transforming the number of statements per coding category per rater to percentages in order to correct for between-subject variance in verbosity and elaboration of answers.
To correct for between-subject and between-session differences in overall response speed, the floor RT was subtracted from the median cap for each condition, yielding the RT cap − floor differential.
To correct for between-subject differences in intracranial volume (volume of all classified tissues combined), all baseline and follow-up volumes were expressed as a percentage of intracranial volume.
To correct for between-subject variability in urine dilution, in each sample the hormone concentration (expressed in ng/l) was divided by the creatinine concentration (expressed in mg/l).
Background correction is platform specific, helps to remove nonspecific signal from total signal and corrects for between-array artefacts.
Write better and faster with AI suggestions while staying true to your unique style.
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