SMILEPLOT: Stata module to create plots for use with multiple significance tests
Roger B. Newson · RePEc: Research Papers in Economics · 2002
This package contains the programs multproc, smileplot and smileplot7. multproc inputs a data set with 1 observation for each of a set of multiple significance tests and data on the P-values, and carries out a multiple test procedure chosen by the user to define a corrected overall critical P-value for accepting or rejecting the null hypotheses tested. These procedures may be one-step, step-up or step-down, and may control the familywise error rate (eg the Bonferroni, Sidak, Holm, Holland-Copenhaver, Hochberg and Rom procedures) or the false discovery rate (eg the Simes, Benjamini-Liu, Benjamini-Yekutieli and Benjamini-Krieger-Yekutieli procedures). smileplot, and its Stata 7 version smileplot7, work by calling multproc and then creating a smile plot, with data points corresponding to multiple estimated parameters, the P-values (on a reverse log scale) on the Y-axis, and the corresponding parameter estimates (or another variable) on the X-axis. There are Y-axis reference lines at the uncorrected and corrected overall critical P-values. The reference line at the corrected critical P-value, known as the parapet line, is interpreted informally as a boundary between data mining and data dredging. multproc, smileplot and smileplot7 are used on data sets with one observation per estimated parameter and data on estimates and their P-values, which may be created using parmby, parmest, statsby or postfile.