Analysis of Dynamic Longitudinal Categorical Data in Incomplete Contingency Tables Using Capture-Recapture Sampling: A case Study of Semi-Concentrated Doctoral Exam
In this paper, dynamic longitudinal categorical data and estimation of their parameters in incomplete contingency tables are evaluated. To apply the proposed method, a study has been conducted on the data of the semi-concentrated doctoral exam of the National Organization for Educational Testing (NOET). The results of studies such as the obtained confidence intervals and calculating the efficiency of estimators show the superiority of the proposed method over other current methods.
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