Frequentist q-values for multiple-test procedures
Multiple-test procedures are increasingly important as technology in- creases scientists’ ability to make large numbers of multiple measurements, as they do in genome scans. Multiple-test procedures were originally defined to input a vector of input p-values and an uncorrected critical p-value, interpreted as a fami- lywise error rate or a false discovery rate, and to output a corrected critical p-value and a discovery set, defined as the subset of input p-values that are at or below the corrected critical p-value. A range of multiple-test procedures is implemented us- ing the smileplot package in Stata (Newson and the ALSPAC Study Team 2003, Stata Journal 3: 109–132; 2010, Stata Journal 10: 691–692). The qqvalue com- mand uses an alternative formulation of multiple-test procedures, which is also used by the R function p.adjust. qqvalue inputs a variable of p-values and out- puts a variable of q-values that are equal in each observation to the minimum familywise error rate or false discovery rate that would result in the inclusion of the corresponding p-value in the discovery set if the specified multiple-test pro- cedure was applied to the full set of input p-values. Formulas and examples are presented. Copyright 2010 by StataCorp LP.
Volume (Year): 10 (2010)
Issue (Month): 4 (December)
|Note:||to access software from within Stata, net describe http://www.stata-journal.com/software/sj10-4/st0209/|
|Contact details of provider:|| Web page: http://www.stata-journal.com/ |
|Order Information:||Web: http://www.stata-journal.com/subscription.html|
When requesting a correction, please mention this item's handle: RePEc:tsj:stataj:v:10:y:2010:i:4:p:568-584. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum)or (Lisa Gilmore)
If references are entirely missing, you can add them using this form.