Information Component computations

When you specify data mining parameters for an MGPS run, you can include Information Component (IC) computations.

The IC is a measure of disproportionality between the observed and expected number of reports for a drug-event combination. A positive IC indicates that the number of observed reports is greater than the number of expected reports. Similarly, a negative IC indicates that the number of observed reports is less than the number of expected reports.

Empirica Signal computes IC values only for drug-event combinations. For example, if you create a three-dimensional MGPS run, Empirica Signal computes IC values for each drug-event combination, and disregards the following:

Combinations of one drug and two events.
Combinations of two drugs and one event.
Combinations of three drugs.
Combinations of three events.

IC values include the following:

IC—Information component
IC025—Lower limit of the 95 percent confidence interval for IC
IC975—Upper limit of the 95 percent confidence interval for IC

If you selected stratification variables for the run, the expected number of reports (E) is adjusted using the Mantel-Haenszel approach. For more information, see Using stratification variables.

If you defined a subset variable for the run, Empirica Signal computes results for each value of the subset variable with observed cases in the data.

Drug-event combination scores

1. Empirica Signal determines the observed counts for each drug-event combination as follows:

	Drug of interest	All other drugs
Event of interest	a	b
All other events	c	d

a—Number of reports of the drug of interest and the event of interest.
b—Number of reports of the event of interest and not the drug of interest.
c—Number of reports of the drug of interest and not the event of interest.
d—Number of reports of neither the event or drug of interest.

2. Empirica Signal computes the expected counts for each drug-event combinations as follows:

	Drug of interest	All other drugs
Event of interest	E(a)=((a+b)(a+c))/(a+b+c+d)	E(b)=((a+b)(b+d))/(a+b+c+d)
All other events	E(c)=((c+d)(a+c))/(a+b+c+d)	E(d)=((c+d)(b+d))/(a+b+c+d)

Note: If you specify a stratification variable for the run, Empirica Signal adjusts the expected count (E) using the Mantel-Haenszel approach. For more information, see Using stratification variables.

3. Empirica Signal computes the IC and IC confidence interval for each drug-event combination as follows:

IC = log2 ((O + α1) / (E + α2))

IC025 = log2 ((O + α1) / (E + α2)) - 3.3 * (O + α1)-1/2 - 2 * (O+ α1)-3/2

IC975 = log2 ((O + α1) / (E + α2)) - 2.4 * (O + α1)-1/2 - .5 * (O+ α1)-3/2

where:

α1=α2= 1/2
O is the observed count.
E is the expected count.