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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Mle And Eap Methods For Estimating Ability Scores For Data Of Varying Sample Size And Item Length, Sahar Taji
Mle And Eap Methods For Estimating Ability Scores For Data Of Varying Sample Size And Item Length, Sahar Taji
Graduate Theses and Dissertations
In this research, the performance of two popular estimators, Maximum Likelihood Estimator(MLE) and Bayesian Expected a Posteriori (EAP) is studied and compared in estimating the latent ability score in an Item Response Theory (IRT) model. The 2-Parameter Logistic (2PL) IRT model which is characterized by difficulty and discrimination item parameters is used to estimate the latent ability scores. Several datasets are generated for variety of sample size and item length values. The Monte-Carlo simulation is used to analyze the performance of the estimators. Results show that MLE produces reliable results with low root mean square error (RMSE) across all datasets. …
Comparing Elo, Glicko, Irt, And Bayesian Irt Statistical Models For Educational And Gaming Data, Breanna Morrison
Comparing Elo, Glicko, Irt, And Bayesian Irt Statistical Models For Educational And Gaming Data, Breanna Morrison
Graduate Theses and Dissertations
Statistical models used for estimating skill or ability levels often vary by field, however their underlying mathematical models can be very similar. Differences in the underlying models can be due to the need to accommodate data with different underlying formats and structure. As the models from varying fields increase in complexity, their ability to be applied to different types of data may have the ability to increase. Models that are applied to educational or psychological data have advanced to accommodate a wide range of data formats, including increased estimation accuracy with sparsely populated data matrices. Conversely, the field of online …