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Machine Learning from Weak Supervision - An Empirical Risk Minimization Approach (Hardcover): Masashi Sugiyama, Han Bao Machine Learning from Weak Supervision - An Empirical Risk Minimization Approach (Hardcover)
Masashi Sugiyama, Han Bao
R1,878 R1,665 Discovery Miles 16 650 Save R213 (11%) Ships in 9 - 15 working days
Differential Item Function Amplification and Cancellation (Paperback): Han Bao Differential Item Function Amplification and Cancellation (Paperback)
Han Bao
R1,779 Discovery Miles 17 790 Ships in 10 - 15 working days

Many educational tests use testlets as a way of providing context. When testlet effect and item idiosyncratic features of individual items are both considered to be the reasons of DIF in many educational tests using testlets, it is interesting to investigate the phenomena of DIF amplification and cancellation resulting from the interactive effects of these two factors. This research presented a study based on a multiple-group testlet item response theory model to examine in detail different situations of DIF amplification and cancellation at the item and testlet level using testlet characteristic curve procedures with signed/ unsigned area indices and logistic regression procedure. The testlet DIF model was estimated using a hierarchical Bayesian framework with the Markov Chain Monte Carlo method. The simulation study investigated all of the possible conditions of DIF amplification and cancellation. Real data analysis indicated the existence of testlet effect and its magnitudes of difference on the means and/or variance of testlet distribution between manifest groups such as gender or ethnicity.

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