The phrase "binary categorisation of" is correct and usable in written English.
It can be used when discussing the classification of items, concepts, or data into two distinct categories.
Example: "The binary categorisation of the data allowed for a clearer analysis of the results."
Alternatives: "dual classification of" or "twofold categorization of".
The scoring of these traits is dominated by the binary categorisation of 'normal' and 'abnormal' and for such binary traits in a liability model, heritability will increase with prevalence.
A further limitation is that the binary categorisation of patients' responses condenses the patients' experiences (which were already limited to several multiple choice options) and may mask potentially significant variations.
Although the use of bootstrap estimation means that inference is appropriate, we also performed a sensitivity analysis based on a binary categorisation of primary-care interval into 0 14 and 15+ days.
Overall, the criteria impose an artificial binary categorisation of the geographic context (allopatric or sympatric) and the stage of speciation (complete or incomplete), both of which in fact represent continua [ 21, 24].
A binary categorisation of private providers was constructed, combining all non-public sector providers (private hospitals/clinics, private doctor's offices and other private medical facilities, including non-governmental organisations).
Furthermore, the binary categorisation of patients' responses, as per DH Survey Guidance, condenses the patients' experiences (which were already limited to several multiple choice options) and may mask potentially significant variations.
Wherever possible, we used continuous variables in preference to binary categorisations of variables due to their greater information content.
Measures of patient experience included in NCPES are reported publicly, both for England as a whole and also by each hospital, and fed back to health service managers and clinical teams using binary categorisations for more or less positive patient experience (Department of Health, 2010a; Quality Health, 2010b).
Although this binary categorisation helps to cut through much of the complexity of skilled migration policy, it does not accommodate recent policy reforms in several OECD countries.
"Public opinion on social issues defies binary categorisation, it is more accurately understood in terms of a continuum, with a middle ground on may issues that comprises more than half the sample.
More subtle, transient moments of ambiguity, which required the shaping of patients' accounts into an inflexible (often binary) categorisation, were common (eg, a patient's hesitant 'not really' becomes 'no'no
