**Chapter
6 Glossary**

**sensitive****, sensitivity: **a
measure's ability to detect differences among participants on a given variable.
(p. 197)

**ceiling effect: **The effects of the treatment or combination
of treatments is underestimated because the dependent measure places too low a
ceiling on what the highest response can be. (p. 204)

**floor**** effect: **the effect of a
treatment or combination of treatments is underestimated because the dependent
measure is not sensitive to values below a certain level. In other words, the
"floor" for low scores is too high. (p. 204)

**nominal**** scale numbers: **numbers
that substitute for names. Different numbers represent *different *types,
kinds, categories, or qualities, but larger numbers do __not__ represent more of a quality than smaller
numbers. (p. 207)

**ordinal**** scale numbers: **numbers
that can be meaningfully ordered from lowest to highest. With ordinal numbers, we
know that the higher scoring participant has *more *of a quality than the
lower scoring participant, but we don't know how much more of the quality the
higher scoring participant has. (p. 208)

**interval**** scale data: **data
for which equal numerical intervals represent equal psychological intervals. That
is, the difference between scoring a "2" and a "1" and the difference between
scoring a "7" and a "6" is the same not only in terms of scores (both are a
difference of 1), but also in terms of the actual amount of the psychological
characteristic being measured. Interval scale measures allow us to compare
participants in terms of *how much *of a quality they have. (p. 209)

**ratio**** scale numbers: **numbers
having all the qualities of interval scale numbers, but that also result from a
measure that has an absolute zero (zero on the measure means the complete absence
of the quality). As the name implies, ratio scale numbers allow you to make
ratio statements about the quality that you are measuring (Steve is two *times
as *friendly as Tom). (p. 211)

**face**** validity: **the extent
to which a measure looks valid to the ordinary person. Face validity has nothing
to do with scientific validity. However, for practical or political reasons,
you may decide to consider face validity when comparing measures. (p.220)