Abstract

Test theories can be divided roughly into two categories. The first is classical test theory, which dates back to Spearman’s conception of the observed test score as a composite of true and error components, and which was introduced to psychologists at the beginning of this century. Important milestones in its long and venerable tradition are Gulliksen’s Theory of Mental Tests (1950) and Lord and Novick’s Statistical Theories of Mental Test Scores (1968). The second is item response theory, or latent trait theory, as it has been called until recently. At the present time, item response theory (IRT) is having a major impact on the field of testing. Models derived from IRT are being used to develop tests, to equate scores from nonparallel tests, to investigate item bias, and to report scores, as well as to address many other pressing measurement problems (see, e.g., Hambleton, 1983; Lord, 1980). IRT differs from classical test theory in that it assumes a different relation of the test score to the variable measured by the test. Although there are parallels between models from IRT and psychophysical models formulated around the turn of the century, only in the last 10 years has IRT had any impact on psychometricians and test users. Work by Rasch (1980/1960), Fischer (1974), 9 Birnbaum (1968), ivrighi and Panchapakesan (1969), Bock (1972), and Lord (1974) has been especially influential in this turnabout; and Lazarsfeld’s pioneering work on latent structure analysis in sociology (Lazarsfeld, 1950; Lazarsfeld & Henry, 1968) has also provided impetus. One objective of this introduction is to review the conceptual differences between classical test theory and IRT. A second objective is to introduce the goals of this special issue on item response theory and the seven papers. Some basic problems with classical test theory are reviewed in the next section. Then, IRT approaches to educational and psychological measurement are presented and compared to classical test theory. The final two sections present the goals for this special issue and an outline of the seven invited papers.

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