comorbidity: Convert base rates of two diagnoses and their comorbidity...

Description Usage Arguments Value Author(s) See Also Examples

Description

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.

Usage

1
comorbidity(d1, d2, com, labels = NULL)

Arguments

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

Value

twobytwo

The two by two table implied by the input

phi

Phi coefficient of the two by two table

Yule

Yule coefficient of the two by two table

tetra

Tetrachoric coefficient of the two by two table

Author(s)

William Revelle

See Also

phi, phi2tetra ,Yule, Yule.inv Yule2phi, tetrachoric and polychoric, as well as AUC for graphical displays

Examples

1
comorbidity(.2,.15,.1,c("Anxiety","Depression")) 

Example output

Call: comorbidity(d1 = 0.2, d2 = 0.15, com = 0.1, labels = c("Anxiety", 
    "Depression"))
Comorbidity table 
            Anxiety -Anxiety
Depression      0.1     0.05
-Depression     0.1     0.75

implies phi =  0.49  with Yule =  0.87  and tetrachoric correlation of  0.75
and normal thresholds of  1.04 0.84

psych documentation built on June 19, 2021, 1:06 a.m.