Seven reasons why you should not categorize continuous data.
I have shown that there are a variety of logical, philosophical, measurement, and statistical reasons why every attempt should be made to measure continuous attributes using measures which reflect that continuity and that following statistical analyses should also retain that continuity. I encourage you to look back at some of the research articles which you have read and see if any of these issues is pertinent. Check out the conclusions and see if they are warranted by the data.
Dinero
T E
TE
Kent State University, USA.
D003627:Data Interpretation, Statistical; D006302:Health Services Research / Q000379:methods* / Q000592:standards; D006801:Humans; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care; D015203:Reproducibility of Results; D012107:Research Design / Q000592:standards; D014481:United States