What question (or questions) are you trying to answer? Any advice we may give will depend on what you are trying to accomplish.
On Sat, Sep 14, 2013 at 2:12 PM, Saumya Gupta <[email protected]>wrote: > I have a dataset which has several predictor variables and a dependent > variable, "score" (which is numeric). The score for each row is calculated > using a formula which uses some of the predictor variables. But, the > "score" figures are not explicitly given in the dataset. The scores are > only arranged in ascending order, and the ranks of the numbers are given > (like 1, 2, 3, 4, etc.; rank 1 means that the particular row had the > highest score, 2 means it had the second highest score and so on). So, if > the data has 100 rows, the output has ranks from 1 to 100. > I don't think it would be proper to treat the output column as a numeric > one, since it is an ordinal variable, and the distance (difference in > scores) between ranks 1 and 2 may not be the same as that between ranks 2 > and 3. However, most R regression models for ordinal regression are made > for output such as (high, medium, low), where each level of the output does > not necessarily correspond to a unique row. In my case, each output (rank) > corresponds to a unique row. > So please suggest me what models I could use for this problem. Will > treating the output as numeric instead of ordinal be a reasonable > approximation? Or will the usual models for ordinal regression work on this > dataset as well? > [[alternative HTML version deleted]] > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Gregory (Greg) L. Snow Ph.D. [email protected] [[alternative HTML version deleted]] ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
