RFET {PhViD}

Reporting Fisher's Exact Test

Description

This function proposes the Fisher's Exact Test as an alternative to the PRR and ROR methods. The statistic of interest is the P-value or the mid-P-value resulting from the test (Ahmed et al., Biometrics).

Usage

RFET(DATABASE, OR0 = 1, MIN.n11 = 1, DECISION = 1, 
DECISION.THRES = 0.05, MID.PVAL = FALSE)

Arguments

DATABASE

Object returned by the function as.PhViD.

OR0

Value of the tested odds ratio. By default, OR0=1.

MIN.n11

Minimum number of notifications for a couple to be potentially considered as a signal. By default, MIN.n11 = 1.

DECISION

Decision rule for the signal generation based on

1 = FDR (Default value)

2 = Number of signals

3 = P-values or mid-P-values. See MID.PVAL

DECISION.THRES

Threshold for DECISION. Ex 0.05 for FDR (DECISION=1).

MID.PVAL

if MID.PVAL=TRUE, the statistic of interest becomes the mid-P-values instead of the P-values resulting from the Fisher's exact test. By default MID.PVAL=FALSE.

Details

The FDR is estimated with the LBE procedure proposed by Dalmasso et al. (2005).

Value

ALLSIGNALS

Data.frame summarizing the results of all couples with at least MIN.n11 notifications ordered by RANKSTAT. It contains notably the labels, the cell counts, the expected count (n1. \times n.1 / N, see as.PhViD), RANKSTAT, the observed odds ratio (ROR), the marginal counts and the estimation of FDR.

SIGNALS

Same Data.frame as ALLSIGNALS but restricted to the list of generated signals.

NB.SIGNALS

Number of generated signals.

INPUT.PARAM

Parameters entered in the function.

Author(s)

Ismaïl Ahmed & Antoine Poncet

References

Ahmed I, Dalmasso C, Haramburu F, Thiessard F, Broët P, Tubert-Bitter P. False discovery rate estimation for frequentist pharmacovigilance signal detection methods. Biometrics. 2010 Mar;66(1):301-309.

Dalmasso C, Broët P, Moreau T (2005), A simple procedure for estimating the false discovery rate, Bioinformatics, Bioinformatics, 21: 660 - 668.

Examples

## start
#data(PhViDdata.frame)
#PhViDdata <- as.PhViD(PhViDdata.frame)
#res <- RFET(PhViDdata)
## end