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Rasch Models Of Multidimensionality Between Items And Within Items, W Wen-Chung, M Wilson, Ray Adams
Rasch Models Of Multidimensionality Between Items And Within Items, W Wen-Chung, M Wilson, Ray Adams
Prof Ray Adams
This chapter focuses on Rasch measurement and extends it to multidimensional Rasch models. The author first clarifies multidimensionality at two levels: the item level and the test level. With this two way classification, three kinds of tests are formed: undimensional tests, multidimensional between-item tests, and multidimensional within-item tests. The author describes a multidimensional Rasch model, the multidimensional random coefficients multinomial logit (MRCML) model, for multidimensional tests. The model, when applied to multidimensional between-item tests, is more efficient than are unidimensional models in terms of model fit and reliability indices. The model can also be applied to investigate scale interaction of …
Bias In Weighted Likelihood Estimation When Using The Rasch Model, D Roberts, Ray Adams
Bias In Weighted Likelihood Estimation When Using The Rasch Model, D Roberts, Ray Adams
Prof Ray Adams
There are three methods of maximum likelihood estimation that are commonly used with Rasch item response models: Joint maximum likelihood, which provides point estimates for both person and item parameters; conditional maximum likelihood, which produces estimates for the item parameters only, and marginal maximum likelihood, which produces estimates of the item parameters and parameters of the distribution from which it has been assumed that the persons have been sampled. A number of approaches have been suggested for obtaining ability estimates for subsequent use in reporting or analysis when either conditional or marginal methods have been used to obtain the item …