The<unk>  effect" is one type of scale attenuation effect; the other scale attenuation effect is the "floor effect". The<unk> is observed when an independent variable no longer has an effect on a dependent variable, or the level above which variance in an independent variable is no longer measurable. The specific application varies slightly in differentiating between two areas of use for this term: pharmacological or statistical. An example of use in the first area, a<unk> in treatment, is pain relief by some kinds of analgesic drugs, which have no further effect on pain above a particular dosage level (see also:<unk> in pharmacology). An example of use in the second area, a<unk> in data-gathering, is a survey that groups all respondents into income categories, not distinguishing incomes of respondents above the highest level measured in the survey instrument. The maximum income level able to be reported creates a<unk> " that results in measurement inaccuracy, as the dependent variable range is not inclusive of the true values above that point. The<unk> can occur any time a measure involves a set range in which a normal distribution predicts multiple scores at or above the maximum value for the dependent variable.
Ceiling effect 
Spectrum bias
Widowhood effect
Weekend effect
Bystander effect 
Age bias 
Publication bias
Martha Mitchell effect