pvda (version 0.0.4)

ror: Reporting Odds Ratio

Description

Calculates Reporting Odds Ratio ("ROR") and confidence intervals, used in disproportionality analysis.

Usage

ror(a = NULL, b = NULL, c = NULL, d = NULL, conf_lvl = 0.95)

Value

A tibble with three columns (point estimate and credibility bounds). Number of rows equals length of inputs a, b, c, d.

Arguments

a

Number of reports for the specific drug and event (i.e. the observed count).

b

Number of reports with the drug, without the event

c

Number of reports without the drug, with the event

d

Number of reports without the drug, without the event

conf_lvl

Confidence level of confidence or credibility intervals. Default is 0.95 (i.e. 95 % confidence interval).

Details

The ROR is an odds ratio calculated from reporting counts. The R for Reporting in ROR is meant to emphasize an interpretation of reporting, as the ROR is calculated from a reporting database. Note: the function is vectorized, i.e. a, b, c and d can be vectors, see the examples.

A reporting odds ratio is simply an odds ratio based on adverse event reports. $$\hat{ROR} = \frac{a/b}{c/d}$$

where \(a\) = observed count (i.e. number of reports with exposure and outcome), \(b\) = number of reports with the drug and without the event, \(c\) = number of reports without the drug with the event and \(d\) = number of reports with neither of the drug and the event.

A confidence interval for the ROR can be derived through the delta method, with a standard deviation:

$$\hat{s} = \sqrt{1/a + 1/b + 1/c + 1/d}$$

with the resulting confidence interval for significance level \(\alpha\)

$$[\hat{ROR} \times exp(\Phi_{\alpha/2} \times \hat{s}), \hat{ROR} \times exp(\Phi_{1-\alpha/2} \times \hat{s})]$$

References

Montastruc_2011pvda

Examples

ror(
  a = 5,
  b = 10,
  c = 20,
  d = 10000
)

# Note that a, b, c and d can be vectors (of equal length, no recycling)
pvda::ror(
  a = c(5, 10),
  b = c(10, 20),
  c = c(15, 30),
  d = c(10000, 10000)
)