  The issue of missing values is an arising difficulty when dealing with paired
data. Several test procedures are developed in the literature to tackle this
problem. Some of them are even robust under deviations and control type-I error
quite accurately. However, most these methods are not applicable when missing
values are present only in a single arm. For this case, we provide asymptotic
correct resampling tests that are robust under heteroscedasticity and skewed
distributions. The tests are based on a clever restructuring of all observed
information in a quadratic form-type test statistic. An extensive simulation
study is conducted exemplifying the tests for finite sample sizes under
different missingness mechanisms. In addition, an illustrative data example
based on a breast cancer gene study is analyzed.
