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. Several of the methods with the same name will work on objects of their respective class. One exception to this rule is the difference between update and EBupdate (described below). Because of the differences in the testing procedures, separately named methods were chosen to clearly delineate which method was being applied to which type of object.
MTP and EBMTP classes, which operates selectively on each slot of an MTP or EBMTP instance to retain only the data related to the specified hypotheses.MTP or EBMTP to an object of class list, with an entry for each slot.MTP and EBMTP classes, produces the following graphical summaries of the results of a MTP. The type of display may be specified via the which argument. 1. Scatterplot of number of rejected hypotheses vs. nominal Type I error rate. 2. Plot of ordered adjusted p-values; can be viewed as a plot of Type I error rate vs. number of rejected hypotheses. 3. Scatterplot of adjusted p-values vs. test statistics (also known as volcano plot). 4. Plot of unordered adjusted p-values. Only for objects of class MTP: 5. Plot of confidence regions for user-specified parameters, by default the 10 parameters corresponding to the smallest adjusted p-values (argument top). 6. Plot of test statistics and corresponding cut-offs (for each value of alpha) for user-specified hypotheses, by default the 10 hypotheses corresponding to the smallest adjusted p-values (argument top). Plots (5) and (6) are not available for objects of class EBMTP because the function EBMTP returns only adjusted p-values and not confidence regions of cut-offs. The argument logscale (by default equal to FALSE) allows one to use the negative decimal logarithms of the adjusted p-values in the second, third, and fourth graphical displays. The arguments caption and sub.caption allow one to change the titles and subtitles for each of the plots (default subtitle is the MTP function call). Note that some of these plots are implemented in the older function mt.plot.MTP and EBMTP classes, returns a description of an object of either class, including sample size, number of tested hypotheses, type of test performed (value of argument test), Type I error rate (value of argument typeone), nominal level of the test (value of argument alpha), name of the MTP (value of argument method), call to the function MTP or EBMTP. In addition, this method produces a table with the class, mode, length, and dimension of each slot of the MTP or EBMTP instance.
MTP and EBMTP classes, provides numerical summaries of the results of a MTP and returns a list with the following three components. 1. rejections: A data.frame with the number(s) of rejected hypotheses for the nominal Type I error rate(s) specified by the alpha argument of the function MTP or EBMTP. (For objects of class MTP, NULL values are returned if all three arguments get.cr, get.cutoff, and get.adjp are FALSE). 2. index: A numeric vector of indices for ordering the hypotheses according to first adjp, then rawp, and finally the absolute value of statistic (not printed in the summary). 3. summaries: When applicable (i.e., when the corresponding quantities are returned by MTP or EBMTP), a table with six number summaries of the distributions of the adjusted p-values, unadjusted p-values, test statistics, and parameter estimates.MTP class, respectively, provides a mechanism to re-run the MTP with different choices of the following arguments - nulldist, alternative, typeone, k, q, fdr.method, alpha, smooth.null, method, get.cr, get.cutoff, get.adjp, keep.nulldist, keep.rawdist, keep.margpar. When evaluate is 'TRUE', a new object of class MTP is returned. Else, the updated call is returned. The MTP object passed to the update method must have either a non-empty rawdist slot or a non-empty nulldist slot (i.e., must have been called with either 'keep.rawdist=TRUE' or 'keep.nulldist=TRUE').EBMTP class, provides a mechanism to re-run the MTP with different choices of the following arguments - nulldist, alternative, typeone, k, q, alpha, smooth.null, bw, kernel, prior, keep.nulldist, keep.rawdist, keep.falsepos, keep.truepos, keep.errormat, keep.margpar. When evaluate is 'TRUE', a new object of class EBMTP is returned. Else, the updated call is returned. The EBMTP object passed to the update method must have either a non-empty rawdist slot or a non-empty nulldist slot (i.e., must have been called with either 'keep.rawdist=TRUE' or 'keep.nulldist=TRUE'). Additionally, when calling EBupdate for any Type I error rate other than FWER, the typeone argument must be specified (even if the original object did not control FWER). For example,
typeone="fdr", would always have to be specified, even if the original object also controlled the FDR. In other words, for all function arguments, it is safest to always assume that you
are updating from the EBMTP default function settings, regardless of the original call to the EBMTP function. Currently, the main advantage of the EBupdate method is that it prevents the need for repeated estimation of the test statistics null distribution. To save on memory, if one knows ahead of time that one will want to compare different choices of bootstrap-based null distribution, then it is both necessary and sufficient to specify 'keep.rawdist=TRUE', as there is no other means of moving between null distributions other than through the non-transformed non-parametric bootstrap distribution. In this case, 'keep.nulldist=FALSE' may be used. Specifically, if an object of class MTP or EBMTP contains a non-empty rawdist slot and an empty nulldist slot, then a new null distribution will be generated according to the values of the nulldist= argument in the original call to (EB)MTP or any additional specifications in the call to (EB)update. On the other hand, if one knows that one wishes to only update an (EB)MTP object in ways which do not involve choice of bootstrap null distribution, then 'keep.nulldist=TRUE' will suffice and 'keep.rawdist' can be set to FALSE (default settings). The original null distribution object will then be used for all subsequent calls to update. N.B.: Note that keep.rawdist=TRUE is only available for the bootstrap-based resampling methods. The non-null distribution does not exist for the permutation or influence curve multivariate normal null distributions.
MTP to objects of class EBMTP. Slots common to both objects are taken from the object of class MTP and used to create a new object of class EBMTP. Once an object of class EBMTP is created, one may use the method EBupdate to perform resampling-based empirical Bayes multiple testing without the need for repeated resampling.EBMTP to objects of class MTP. Slots common to both objects are taken from the object of class EBMTP and used to create a new object of class MTP. Once an object of class MTP is created, one may use the method update to perform resampling-based multiple testing (as would have been done with calls to MTP) without the need for repeated resampling.