EBMTP-class
(Package: multtest) :
Class "EBMTP", classes and methods for empirical Bayes multiple testing procedure output
An object of class EBMTP is the output of a particular multiple testing procedure, as generated by the function EBMTP. The object has slots for the various data used to make multiple testing decisions, in particular adjusted p-values.
EBMTP
(Package: multtest) :
A function to perform empirical Bayes resampling-based multiple hypothesis testing
A user-level function to perform empirical Bayes multiple testing procedures (EBMTP). A variety of t- and F-tests, including robust versions of most tests, are implemented. A common-cutoff method is used to control the chosen type I error rate (FWER, gFWER, TPPFP, or FDR). Bootstrap-based null distributions are available. Additionally, for t-statistics, one may wish to sample from an appropriate multivariate normal distribution with mean zero and correlation matrix derived from the vector influence function. In EBMTP, realizations of local q-values, obtained via density estimation, are used to partition null and observed test statistics into guessed sets of true and false null hypotheses at each round of (re)sampling. In this manner, parameters of any type I error rate which can be expressed as a function the number of false positives and true positives can be estimated. Arguments are provided for user control of output. Gene selection in microarray experiments is one application.
Hsets
(Package: multtest) :
Functions for generating guessed sets of true null hypotheses in empirical Bayes resampling-based multiple hypothesis testing
These functions are called internally by the main user-level function EBMTP. They are used for estimating local q-values, generating guessed sets of true null hypotheses, and applying these results to function closures defining the choice of type I error rate (FWER, gFWER, TPPFP, and FDR).
MTP-class
(Package: multtest) :
Class "MTP", classes and methods for multiple testing procedure output
An object of class MTP is the output of a particular multiple testing procedure, for example, generated by the MTP function. It has slots for the various data used to make multiple testing decisions, such as adjusted p-values and confidence regions.
MTP-methods
(Package: multtest) :
Methods for MTP and EBMTP objects in Package `multtest'
Summary, printing, plotting, subsetting, updating, as.list and class conversion methods were defined for the MTP and EBMTP classes. These methods provide visual and numeric summaries of the results of a multiple testing procedure (MTP) and allow one to perform some basic manipulations of objects class MTP or EBMTP.
MTP
(Package: multtest) :
A function to perform resampling-based multiple hypothesis testing
A user-level function to perform multiple testing procedures (MTP). A variety of t- and F-tests, including robust versions of most tests, are implemented. Single-step and step-down minP and maxT methods are used to control the chosen type I error rate (FWER, gFWER, TPPFP, or FDR). Bootstrap and permutation null distributions are available. Additionally, for t-statistics, one may wish to sample from an appropriate multivariate normal distribution with mean zero and correlation matrix derived from the vector influence function. Arguments are provided for user control of output. Gene selection in microarray experiments is one application.
boot.null
(Package: multtest) :
Non-parametric bootstrap resampling function in package `multtest'
Given a data set and a closure, which consists of a function for computing the test statistic and its enclosing environment, this function produces a non-parametric bootstrap estimated test statistics null distribution. The observations in the data are resampled using the ordinary non-parametric bootstrap is used to produce an estimated test statistics distribution. This distribution is then transformed to produce the null distribution. Options for transforming the nonparametric bootstrap distribution include center.only, center.scale, and quant.trans. Details are given below. These functions are called by MTP and EBMTP.
corr.null
(Package: multtest) :
Function to estimate a test statistics joint null distribution for t-statistics via the vector influence curve
For a broad class of testing problems, such as the test of single-parameter null hypotheses using t-statistics, a proper, asymptotically valid test statistics joint null distribution is the multivariate Gaussian distribution with mean vector zero and covariance matrix equal to the correlation matrix of the vector influence curve for the estimator of the parameter of interest. The function corr.null estimates the correlation matrix of the vector influence curve for such parameters and returns samples from the corresponding normal distribution. Arguments to the function allow for refinements in calculating the resulting null distribution estimate.
fwer2gfwer
(Package: multtest) :
Function to compute augmentation MTP adjusted p-values
Augmentation multiple testing procedures (AMTPs) to control the generalized family-wise error rate (gFWER), the tail probability of the proportion of false positives (TPPFP), and false discovery rate (FDR) based on any initial procudeure controlling the family-wise error rate (FWER). AMTPs are obtained by adding suitably chosen null hypotheses to the set of null hypotheses already rejected by an initial FWER-controlling MTP. A function for control of FDR given any TPPFP controlling procedure is also provided.
get.index
(Package: multtest) :
Function to compute indices for ordering hypotheses in Package 'multtest'
The hypotheses tested in a multiple testing procedure (MTP), can be ordered based on the output of that procedure. This function orders hypotheses based on adjusted p-values, then unadjusted p-values (to break ties in adjusted p-values), and finally test statistics (to break remaining ties).
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