Mostly it is a conceptual difference. An unordered factor is one where there is
no inherent order to the levels, examples:
Color of car
Race
Nationality
Sex
State/Country of birth
Etc.
In the above, the order of the levels could be changed without it really
changing the meaning (think of the order of bars in a bar chart). We may want
to print/plot in some specific order such as alphabetic for easy lookup or based
on the summary values of another vector for nice looking plots, but there is no
overriding reason why we would order color as blue/green/red vs. green/red/blue,
etc.
Ordered factors have some natural order, for example maybe you are studying a
drug and have doses labeled as Low, Medium, and High. It makes the most sense
to print and plot in that order rather than alphabetically (High, Low, Medium).
Any continuous variable that has been cut into categories (best not to do this,
but if done) has a natural order. Survey questions where you response can range
from strongly disagree to strongly agree are usually ordered (but there may be
disagreement on what the correct ordering is).
In R the most apparent effects of using ordered vs. factor is in how they print
out and how some modeling functions default to handling them (the default
contrasts for ordered factors is different, rpart treats ordered factors
differently).
Hope this helps,
--
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of Peng Yu
> Sent: Sunday, November 08, 2009 4:28 PM
> To: r-help at stat.math.ethz.ch
> Subject: [R] ordered factor and unordered factor
>
> I don't understand under what situation ordered factor rather than
> unordered factor should be used. Could somebody give me some examples?
> What are the implications of order vs. unordered factors? Could
> somebody recommend a textbook to me?
>
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