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.

Oracle Empirica Signal computes IC values only for drug-event combinations. For example, if you create a three-dimensional MGPS run, Oracle 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 Stratification variables.

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

Drug-event combination scores

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

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

   Event	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, Oracle Empirica Signal adjusts the expected count (E) using the Mantel-Haenszel approach.
3. Oracle 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.