SGoF: Conservative SGoF multiple testing procedure

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/SGoF.R

Description

Performs Conservative SGoF method (de Uña Álvarez, 2011) for multiple hypothesis testing.

Usage

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SGoF(u, alpha = 0.05, gamma = 0.05)

Arguments

u

A (non-empty) numeric vector of p-values.

alpha

Numeric value. The significance level of the metatest.

gamma

Numeric value. The p-value threshold, so Conservative SGoF looks for significance in the amount of p-values below gamma.

Details

Conservative SGoF is an asymptotic version (large number of tests) of the Binomial SGoF procedure, where the binomial quantiles are approximated by the normal ones. Besides, the variance of the number of p-values below gamma is estimated without assuming that all the null hypotheses are true, which typically results in a more conservative decision (from this the method’s name). When the number of tests is large, Conservative SGoF and Binomial SGoF report approximately the same result. This method should no be used when the number of tests is small, because the binomial-normal approximation will perform poorly. Conservative SGoF method has the main properties of Binomial SGoF like weak control of the family-wise error rate (FWER) and the false discovery rate (FDR) at level alpha and a good balance between FDR and power, particularly when the number of tests is large, and the effect level is weak to moderate. See Binomial.SGoF for more details. Typically, the choice alpha=gamma will be used; this common value will be set as one of the usual significance levels (0.001, 0.01, 0.05, 0.1). Note however that alpha and gamma have different roles. The FDR is estimated by the simple method proposed by: Dalmasso, Broet, Moreau (2005), by taking n=1 in their formula. The adjusted p-value of a given p-value pi is defined as the smallest alpha0 for which the null hypothesis attached to pi is rejected by Conservative SGoF with alpha=gamma=alpha0. Actually, Conservative.SGoF function provides these adjusted p-values by restricting alpha0 to the set of original p-values (Castro Conde and de Uña Álvarez , 2015).

Value

A list containing the following values:

Rejections

The number of effects declared by SGoF.

FDR

The estimated false discovery rate.

Adjusted.pvalues

The adjusted p-values.

data

The original p-values.

alpha

The specified significance level for the metatest.

gamma

The specified p-value threshold.

call

The matched call.

Author(s)

Irene Castro Conde and Jacobo de Uña Álvarez

References

Castro Conde I and de Uña Álvarez J (2015). Adjusted p-values for SGoF multiple test procedure. Biometrical Journal; 57(1): 108-122. DOI:10.1002/bimj.201300238.

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

de Uña-Álvarez J (2011). On the statistical properties of SGoF multitesting method. Statistical Applications in Genetics and Molecular Biology, Vol. 10, Iss. 1, Article 18.

See Also

summary.SGoF,plot.SGoF

Examples

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p<-runif(387)^2  #387 independent p-values, non-uniform intersection null violated

res<-SGoF(p)
summary(res)   #number of rejected nulls, estimated FDR
plot(res)   #adjusted p-values

sgof documentation built on May 30, 2017, 6:08 a.m.