# prev

##### The prevalence (baseline probability) of a condition.

`prev`

defines a condition's prevalence value
(or baseline probability):
The probability of the condition being `TRUE`

.

- Keywords
- datasets

##### Usage

`prev`

##### Details

Understanding or obtaining the prevalence value `prev`

:

Definition:

`prev`

is the (non-conditional) probability:`prev = p(condition = TRUE)`

or the base rate (or baseline probability) of the condition's occurrence or truth.

In terms of frequencies,

`prev`

is the ratio of`cond_true`

(i.e.,`hi + mi`

) divided by`N`

(i.e.,`hi + mi`

+`fa + cr`

):`prev = cond_true/N = (hi + mi)/(hi + mi + fa + cr)`

Perspective:

`prev`

classifies a population of`N`

individuals by condition (`prev = cond_true/N`

).`prev`

is the "by condition" counterpart to`ppod`

(when adopting a "by decision" perspective) and to`acc`

(when adopting a "by accuracy" perspective).Alternative names: base rate of condition, proportion affected, rate of condition

`= TRUE`

cases.`prev`

is often distinguished from the*incidence rate*(i.e., the rate of new cases within a certain time period).Dependencies:

`prev`

is a feature of the population and of the condition, but independent of the decision process or diagnostic procedure.While the value of

`prev`

does*not*depend on features of the decision process or diagnostic procedure,`prev`

must be taken into account when computing the conditional probabilities`sens`

,`mirt`

,`spec`

,`fart`

,`PPV`

, and`NPV`

(as they depend on`prev`

).

##### Format

An object of class `numeric`

of length 1.

##### References

Consult Wikipedia for additional information.

##### See Also

`prob`

contains current probability information;
`num`

contains basic numeric variables;
`init_num`

initializes basic numeric variables;
`comp_prob`

computes derived probabilities;
`comp_freq`

computes natural frequencies from probabilities;
`is_prob`

verifies probabilities.

Other probabilities: `FDR`

, `FOR`

,
`NPV`

, `PPV`

, `acc`

,
`err`

, `fart`

,
`mirt`

, `ppod`

,
`sens`

, `spec`

##### Examples

```
# NOT RUN {
prev <- .10 # sets a prevalence value of 10%
prev <- 10/100 # (condition = TRUE) for 10 out of 100 individuals
is_prob(prev) # TRUE
# }
```

*Documentation reproduced from package riskyr, version 0.2.0, License: GPL-2 | GPL-3*