Timeline for Using ordered factor as predictor in R [duplicate]
Current License: CC BY-SA 3.0
11 events
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| Oct 2, 2014 at 16:05 | history | closed |
Scortchi♦ Andy whuber♦ |
Duplicate of Continuous dependent variable with ordinal independent variable | |
| Oct 2, 2014 at 14:58 | comment | added | Scortchi♦ |
@BenBolker: Isn't ordinal concerned with modelling ordinal responses?
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| Oct 2, 2014 at 14:39 | review | Close votes | |||
| Oct 2, 2014 at 16:05 | |||||
| Oct 2, 2014 at 14:34 | comment | added | Scortchi♦ | @Roland: True enough (in R) but that amounts to no more than an alternative coding scheme for a categorical predictor - unless you want to fit only the linear & quadratic, say, contrasts of an ordinal predictor with more than three levels; in which case the considerations raised by MrFlick again become relevant. | |
| Oct 2, 2014 at 14:23 | comment | added | Scortchi♦ | possible duplicate of Continuous dependent variable with ordinal independent variable, Coding for an ordered covariate, & Logistic regression and ordinal independent variables. | |
| Oct 2, 2014 at 13:01 | comment | added | Roland | @MrFlick That's not correct. Ordered factors are modeled using polynomial contrasts by default. | |
| Oct 2, 2014 at 10:12 | answer | added | lyolya | timeline score: 1 | |
| Oct 2, 2014 at 9:13 | history | migrated | from stackoverflow.com (revisions) | ||
| Oct 1, 2014 at 22:22 | comment | added | MrFlick | What sort of modeling procedure do you want to use for an orginal predictor. None of the "standard" linear models use ordinal values any differently than categorical values. You need to include additional assumptions, like do you think the effects of the radiation 1-9 are 2x greater than 0? Is there a linear relationship (or other complicated relationship) between the levels? Are some point you are going to have to map them to numerical values based on additional modeling assumptions. | |
| Oct 1, 2014 at 22:19 | comment | added | Ben Bolker |
how about glm(cbind(leukemia,other)~as.numeric(x),data=leuk,family=binomial("logit")) (oops, not significantly different from your second solution)? Or consider the ordinal package.
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| Oct 1, 2014 at 22:11 | history | asked | Ryan Simmons | CC BY-SA 3.0 |