Classical test theory is concerned with the reliability of a test and
assumes that the items
within the test are sampled at random from a domain of relevant items.
Reliability is seen
as a characteristic of the test and of the variance of the trait it
measures. Items are treated
as random replicates of each other and their characteristics, if
examined at all, are expressed
as correlations with total test score or as factor loadings on the
putative latent variable(s) of
interest. Characteristics of their properties are not analyzed in
detail. This led Mellenbergh
(1996) to the distinction between theories of tests (Lord and Novick,
1968) and a theories
of items (Lord, 1952; Rasch, 1960). The so-called “New Psychometrics”
(Embretson and
Hershberger, 1999; Embretson and Reise, 2000; Van der Linden and
Hambleton, 1997) is a
theory of how people respond to items and is known as Item Response
Theory or IRT. Over
the past twenty years there has been explosive growth in programs that
can do IRT, and
within R there are at least four very powerful packages: eRm (Mair and
Hatzinger, 2007),
ltm Rizopoulos(2006), lme4 (Doran et al., 2007) and MiscPsycho, (Doran,
2010). Additional
packages include mokken (van der Ark, 2010) to do non-metric IRT and
plink (Weeks, 2010)
to link multiple groups together. More IRT packages are being added all
of the time.
Topics covered:
Chapter 8 - The “New Psychometrics” – Item ResponseTheory
Chapter 9 - Validity
Chapter 10 - Reliability + Validity = Structural Equation Models
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