Re: [R] (g)lm ordinal or scaled values?

From: Liaw, Andy <andy_liaw_at_merck.com>
Date: Wed 10 May 2006 - 05:39:42 EST


You got what you got in R because you didn't tell R that the variable is ordinal. You get a bunch of lines when you tell R that var2 is ordinal because the output you get is for the individual coefficients, not the variable. A k-level categorical variable (ordered or otherwise) has associated with it k-1 coefficients (thus the k-1 degrees of freedom). You probably want to do either summary() or anova() on the output of lm() to get the ANOVA table that give you the F-test for the term.

There are good online materials that discuss these basic linear models in R (e.g., http://www.stat.lsa.umich.edu/~faraway/book/), and you would be well-served to peruse them instead of bumping your head on the wall over these confusions.

From: Knut Krueger
>
>
> Liaw, Andy schrieb:
>
> >Ordinal variables should be stored as ordered factors in R.
> See ?ordered.
> >
> thnk`s for your reply. I tried to store as ordered factors
> var <- as.ordered(var2) but if I am calling the
> lm(dependent~var) I get a long list of values.
> If I call
> var <- as.numeric(var2)
> lm(dependent~var)
>
> then I get:
>
> Residuals:
> Min 1Q Median 3Q Max
> -0.93563 0.01378 0.16272 0.25546 0.57862
>
> Coefficients:
> Estimate Std. Error t value Pr(>|t|)
> (Intercept) 1.79513 0.02787 64.412 < 2e-16 ***
> mean -0.28102 0.05993 -4.689 4.66e-06 ***
>
> the SPSS call and Result is:
>
> SPSS (13)
> Analyse
> General Linear Model
> Univariate
> Dependent Variable -> Dependent
> Fixed Factors -> var2
>
> OK
>
>
>
>
> Tests of Between-Subjects Effects
> Dependent Variable: dependent
> | --------------- | ------------------------- | --- | ------------- |
> -------- | ---- |
> | Source | Type III Sum of Squares | df | Mean
> Square | F
> | Sig. |
> | --------------- | ------------------------- | --- | ------------- |
> -------- | ---- |
> | Corrected Model | 11,269(a) | 41 | ,275
>
> | 1,668 | ,012 |
> | --------------- | ------------------------- | --- | ------------- |
> -------- | ---- |
> | Intercept | 361,340 | 1 | 361,340 |
> 2193,088 | ,000 |
> | --------------- | ----------------------- | --- | ----------- |
> -------- | ---- |
> | var2 | 11,269 | 41 | ,275 |
> 1,668 | ,012 |
> | --------------- | ----------------------- | --- | ----------- |
> -------- | ---- |
> | Error | 31,964 | 194 | ,165
> | | |
> | --------------- | ----------------------- | --- | ----------- |
> -------- | ---- |
> | Total | 773,000 | 236 |
> | | |
> | --------------- | ----------------------- | --- | ----------- |
> -------- | ---- |
> | Corrected Total | 43,233 | 235 |
> | | |
> | --------------- | ----------------------- | --- | ----------- |
> -------- | ---- |
> a R Squared = ,261 (Adjusted R Squared = ,104)
>
>
> Maybe anybody is able to show me the difference between SPSS
> and R calls
> because the P value ic complete different
> The url for the Data (if anybody would like to try)
>
> http://biostatistic.de/temp/testr.csv
>
> Regards Knut
>
>
>
>
>
>



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