What is a ceiling effect?

The term "ceiling effect" has two different meanings in
social science research.

First, a ceiling effect is seen
when an independent variable no longer affects a dependent variable after the
independent variable reaches some particular level.  As an example, let's say that the
richer a person becomes, the more likely he or she is to be a Republican.  But let's
also say that once the person's wealth (the independent variable) reaches a certain
level, getting more money (increase in the independent variable) does not make the
person more likely to be a Republican (no more effect on the dependent
variable.

Second, "ceiling effect" can refer to studies in
which a variable is not measured above a certain level.  For example, a survey of how
much money people make might have a last category for $1 million per year
and up.  This is a ceiling effect because the variable
(income) is no longer measured past the $1 million per year
level.