 Classical measurement theory assumes
that some True score (T) exists for the
concept being measured.
 Rarely, if ever, is T directly
observable.
 Instead, our Observed score
(O) composed of T and an Error
component (E):
 To the extent that we reduce
E, our observed score will converge on the true
score of the concept.
 Practical implications of this
assumption for research:
 All observations are
imperfect measures of a concept, due to two
types of error,
 random
 observation errors for
individual cases are unknown but
offsetting
 there is no bias in
estimating T from the mean
O
 systematic
 observation errors are
unknown but not offsetting
 there is bias in
estimating T from the mean
O
 Systematic error in measurement is
difficult to resolve
 resolution depends on the
theory and the problem
 measurement theory literature
offers few formulaic solutions
 Random errorthe common
problemis easier to handle
 The general approach is to use
multiple indicators (composite
measures)
 Sometimes these composite
measures are called a scale, sometimes an
index
