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中文摘要：
最大优先级指标（MPI）选题策略可以较好地满足非统计性约束,按a分层的选题策略可以有效提高低区分度项目的利用率,结合两者的优势,构造了附加区分度约束的两阶段MPI选题策略.Monte Carlo模拟研究表明：新选题策略在题库的未使用率方面有明显改进,在测量精度和约束条件控制等评价指标上较现有方法差异不大.
英文摘要：
MPI can well meet the statistical constraints,and a-stratified method can effectively improve the utilization rate of low discrimination item. Combining the advantages of MPI and a-stratified method,a two-phase MPI item selection strategy with additional distinction constraint is constructed. The simulation study of Monte Carlo shows that the new item selection strategy has improved a lot in the inavailability of item bank,which is about the same as the existing approach in measurement accuracy,constraint management and other evaluation in dices.
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