The phrase 'categorisation of variables' is correct and usable in written English.
It is typically used in mathematics, science, and other technical fields. For example, "Scientists used the categorisation of variables to create a more accurate model of the solar system."
The categorisation of variables is described below.
However, direct comparison of specific variables was not always possible due to different study approaches and categorisation of variables.
One consequence of this was that, categorisation of variables such as RR, enabled an average of 38% of values not to be excluded.
Almost all evidence pertaining to the effect of demographic risk factors was available only for SSD, and limitations included sparse replication and diverse categorisation of variables across studies.
As a result of the categorisation of variables such as age, socio-economic status, questionnaire response and proportion of 50+ in a household, there were very few people in some groups, that is a small increase in absolute numbers resulted in higher percentages.
Wherever possible, we used continuous variables in preference to binary categorisations of variables due to their greater information content.
We used the GSM exposure (the measurement of RF EMF in the bedroom) as a continuous variable because it is recognised that categorisation of continuous variables introduces major problems in the analysis and interpretation of models derived in a data-dependent fashion.
Although the general statistical advice is to keep continuous exposure variables as continuous in statistical analyses [ 1, 2], categorisation of continuous variables is still a common approach in medical research [ 3, 4].
Categorisation of the variables.
Categorisation of continuous variables is commonly used in clinical research.
The categorisation of adjustment variables was prespecified before analysis, with the exception of birth weight.
