multproc carries out multiple-test procedures, taking as input a list of p-values
and an uncorrected critical p-value, and calculating a corrected overall critical pvalue
for rejection of null hypotheses. These procedures define a conÞdence region
for a set-valued parameter, namely the set of null hypotheses that are true. They
aim to control either the family-wise error rate (FWER) or the false discovery
rate (FDR) at a level no greater than the uncorrected critical p-value. smileplot
calls multproc and then creates a smile plot, with data points corresponding to
estimated parameters, the p-values (on a reverse log scale) on the y-axis, and the
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
for the corrected overall critical p-value, known as the parapet line, is an informal
Òupper confidence limitÓ for the set of null hypotheses that are true and defines a
boundary between data mining and data dredging. A smile plot summarizes a set
of multiple analyses just as a Cochrane forest plot summarizes a meta-analysis.
Copyright 2003 by Stata Corporation.