  This study proposes a method of nonresponse assessment based on
meta-analytical file-drawer techniques, also known as worst-case resistance
testing (WCRT), and suitable for a wide range of data collection scenarios. A
general method is devised to estimate the number of significantly different
nonrespondents it would take to significantly alter the results of an analysis.
Estimates of nonrespondents can be plotted against effect sizes using
"n-curves", with similar interpretation to p-curves or power curves. Variants
of the general method are derived for tests of means and correlations. A sample
using a well-established survey instrument from previous behavioral research is
used to test the method. The results suggest that employing worst-case
resistance testing can be used on its own or in conjunction with wave analysis
to precisely flag nonresponse risks.
