English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We propose a novel methodology relating item response theory methods withsmall area estimation strategies in the presence of missing data. Specifically,we propose an unbiased estimator for the average ability parameter ofthree-parameter logistic models. Thus, we carry out an extensive simulationstudy in order to compare our estimator with the well-known Horvitz-Thompsonestimator. According to our experiments with synthetic data, our proposal hassubstantial lower standard errors than its competitor. In addition, we performan actual application by considering the Mathematics results of the 2015Program for International Student Assessment (PISA), and also, compare ourresults with previous analyses. Our findings strongly suggest that ourmethodology is a high competitive alternative for generating compellingofficial statistics.

Small area estimation using multiple imputation in three-parameter logistic models