# R: Interpretation ordinal regression with clm

I have a question regarding the interpretation of an ordinal regression in R with the clm function.

I am new to this and used this formula:

RegADHD <- clm(ADHD$$Score ~ ADHD$$Group)


Score is a ordered factor from 0-3 (0= no symptoms, 3= maximal symptoms)

Group is a group variable with 3 categories (no exposure, less exposure, severe exposure).

With summary I get this:

Coefficients:
Estimate Std. Error z value Pr(>|z|)
ADHD$Group3 1.0422 0.4647 2.242 0.0249 * --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Threshold coefficients: Estimate Std. Error z value 0|1 1.3612 0.3720 3.659 1|2 2.5735 0.4465 5.764 2|3 3.3582 0.5367 6.258 (2 observations deleted due to missingness)  But I don´t really understand what is the interpretation of this coefficient? More specifically, I struggle because I get only one value (for group 3). These are the contrasts of group:  2 3 1 0 0 2 1 0 3 0 1  To get the odds I did: round(exp(RegADHD$beta), 3)


This is 2.835

with(RegADHD, table(ADHD$$Score, ADHD$$Group))


   1   2   3
0  0   34  30
1  0   7  11
2  0   1   5
3  0   1   5


Does this mean that the probability of having a higher score (in ADHD) increases 2.835 times with being in the severe exposure group, compared with no exposure? But then I don´t know anything about less exposure... I don´t understand why I get only one coefficient!

I hope anyone can help me, I am thankful for every advice!

## migrated from stackoverflow.comOct 7 '18 at 8:23

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• As noted by @mdewey , there appears to be something wrong with the Group variable. It looks like it has only two levels. I also suspect you want some output other than that given by summary. To get an anova-like table, try library(car); library(RVAideMemoire); Anova.clm(RegADHD). To get differences between groups, try library(emmeans); emmeans(RegADHD, ~ Group); pairs(emmeans(RegADHD, ~ Group)) – Sal Mangiafico Oct 7 '18 at 15:22
• Looking at the output from with(RegADHD, table(ADHD$Score, ADHD$Group), you have no observations for the first Group. – Sal Mangiafico Oct 7 '18 at 16:44
• Ohh you´re right, I detected my mistake in the configuration of the data frame.. fixed it now, so I have observations for every group and 2 coefficients as I expected. But the question remains: How can I interpret the output from this function? And if we assume I´ll do another with one additional and want to compare both... I can use an anova then I guess? But do I have to be careful with SS or contrasts then? Any advices? – LotteLi Oct 7 '18 at 18:44
• For me, I would tend to look at the output from Anova.clm and emmeans, probably along with the group medians. That's the way I would look at this, like I would a typical anova with post-hoc. But the information from summary may be more meaningful for you. ... When you say do another one and compare both, not sure what you would intend to compare. – Sal Mangiafico Oct 7 '18 at 19:05
• Thanks, what I want to know is: I used treatment contrasts (group 1 is reference). I think this is ok for what I want to know, because group 1 is somewhat like a Baseline. Now in the next step I want to add 4 other variables (all metric) to see if they change the interaction. To compare both models I want to run a Anova then. Can I do this with treatment contrasts? And can I just use anova(model1, model2)? Or is it problematic because of Type I SS (I know this is problematic with unbalanced groups in classical Anova, but does it also hold here?) – LotteLi Oct 8 '18 at 6:48