  Defining the Inclusion/Exclusion (I/E) criteria of a trial is one of the most
important steps during a trial design. Increasingly complex I/E criteria
potentially create information imbalance and transparency issues between the
people who design and run the trials and those who consume the information
produced by the trials. In order to better understand and quantify the impact
of a category of I/E criteria on observed treatment effects, a concept, named
the Selection Induced Contrast Estimate (SICE) effect, is introduced and
formulated in this paper. The SICE effect can exist in controlled clinical
trials when treatment affects the correlation between a marker used for
selection and the response of interest. This effect is demonstrated with both
simulations and real clinical trial data. Although the statistical elements
behind the SICE effect have been well studied, explicitly formulating and
studying this effect can benefit several areas, including better transparency
in I/E criteria, meta-analysis of multiple clinical trials, treatment effect
interpretation in real-world medical practice, etc.
