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PhViD (version 1.0.3)

RFET: 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.

Value

  • ALLSIGNALSData.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.
  • SIGNALSSame Data.frame as ALLSIGNALS but restricted to the list of generated signals.
  • NB.SIGNALSNumber of generated signals.
  • INPUT.PARAMParameters entered in the function.

encoding

UTF-8

Details

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

References

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

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

Examples

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

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