Rasch models for measurement, Issue 68
Measurement models developed by Georg Rasch are renowned in the social sciences. In this introduction, the focus is on the simple logistic model, which is one of the most elementary and commonly used. The author explains the general principles behind the models, and demonstrates their procedures for measurement. Comparisons are made with other more widely-used models. Throughout the text, an example from a personality inventory is used to provide continuity as the statistical arguments are presented and procedures explained.
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Estimation Through Odds
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7rri according achievement testing additive structure affective value algorithm Analysis Andrich artificial example chapter checking conditional estimates conjoint measurement constructed continuum discrimination distribution endorse equation 3.9 equation 5.4 equation 5.9b Figure 6.5b frame of reference function fundamental measurement Guttman pattern Guttman scale Item Parameter Estimates joint estimation likelihood linear location parameter Log-Linear Models males and females method misfit Murdoch University neuroticism number of items number of persons objects observed obtained Odds Ratio outcome space pair of items pair-wise estimation person parameters persons and items probability procedure properties Psychology quantitative Rasch model Raven's Progressive Matrices raw scores relationship replications residuals response patterns sample score groups sexes shown in Table shows simple simultaneous scaling six items social science solution equations specific standard errors Statistical independence sufficient statistic tests of fit Thurstone total score two-way frame unidimensional variable Wright and Stone