dc.contributor.author Pierre Foy en_US
dc.contributor.author Liqun Yin en_US
dc.date.accessioned 2019-08-12T04:59:02Z
dc.date.available 2019-08-12T04:59:02Z
dc.date.issued 2015-12-??
dc.description.abstract Large-scale assessments in education, such as IEA’s TIMSS and PIRLS, rely on sophisticated assessment instruments, elaborate sample designs, and leading-edge item response theory to meet their analytical objectives. Both assessments provide a rich and complex database intended to support and promote secondary analyses. This paper describes the complex international database structures and the statistical methods and procedures for analyzing TIMSS and PIRLS data, with examples provided for illustration. Three essential elements must be considered by researchers in any statistical analysis based on data from the TIMSS and PIRLS international databases. The first is the use of sampling weights in order to produce accurate and reliable results. Second, both assessments apply the Jackknife Repeated Replication technique to derive proper estimates of sampling variance. Finally, with student achievement reported as sets of five plausible values, statistical analyses are performed five times, once for each plausible value, and the final results aggregated across the five plausible values. Researchers and users of the TIMSS and PIRLS international databases who conduct their analyses as described in this paper should feel confident in the results their analyses will yield. en_US
dc.identifier 53C061E9-CB6F-DF70-CD8C-002FB89210FB
dc.identifier.uri http://rportal.lib.ntnu.edu.tw:80/handle/20.500.12235/81275
dc.language 英文
dc.publisher 教育研究與評鑑中心 zh_tw
dc.publisher Center for Educational Research and Evaluation en_US
dc.relation 23(4),41-61
dc.relation.ispartof 當代教育研究 zh_tw
dc.subject.other item response theory en_US
dc.subject.other jackknife repeated replication en_US
dc.subject.other matrix sampling en_US
dc.subject.other multi-stage cluster sampling en_US
dc.subject.other plausible values en_US
dc.subject.other PIRLS en_US
dc.subject.other TIMSS en_US
dc.title.alternative DATA ANALYSES WITH IEA’S TIMSS AND PIRLS INTERNATIONAL DATABASES zh_tw
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