In medicine and clinical psychology, diagnoses tend to be categorical (someone is depressed or not, someone has an anxiety disorder or not). Cooccurrence of both of these symptoms is called comorbidity. Diagnostic categories vary in their degree of comorbidity with other diagnostic categories. From the point of view of correlation, comorbidity is just a name applied to one cell in a four fold table. It is thus possible to analyze comorbidity rates by considering the probability of the separate diagnoses and the probability of the joint diagnosis. This gives the two by two table needed for a phi, Yule, or tetrachoric correlation.

`comorbidity(d1, d2, com, labels = NULL)`

d1

Proportion of diagnostic category 1

d2

Proportion of diganostic category 2

com

Proportion of comorbidity (diagnostic category 1 and 2)

labels

Names of categories 1 and 2

The two by two table implied by the input

Phi coefficient of the two by two table

Yule coefficient of the two by two table

Tetrachoric coefficient of the two by two table

`phi`

, `phi2tetra`

,`Yule`

, `Yule.inv`

`Yule2phi`

, `tetrachoric`

and `polychoric`

, as well as `AUC`

for graphical displays

```
# NOT RUN {
comorbidity(.2,.15,.1,c("Anxiety","Depression"))
# }
```

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