Open AccessJACKKNIFING TECHNIQUES FOR EVALUATION OF EQUATING ACCURACY
Author(s) -
Haberman Shelby J.,
Lee YiHsuan,
Qian Jiahe
Publication year - 2009
Publication title -
ets research report series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.235
H-Index - 5
ISSN - 2330-8516
DOI - 10.1002/j.2333-8504.2009.tb02196.x
Subject(s) - equating , statistics , mathematics , selection (genetic algorithm) , sampling (signal processing) , econometrics , item response theory , stratified sampling , stability (learning theory) , simple random sample , computer science , artificial intelligence , psychometrics , machine learning , filter (signal processing) , rasch model , computer vision , population , demography , sociology
Grouped jackknifing may be used to evaluate the stability of equating procedures with respect to sampling error and with respect to changes in anchor selection. Properties of grouped jackknifing are reviewed for simple‐random and stratified sampling, and its use is described for comparisons of anchor sets. Application is made to examples of item response theory (IRT) true‐score equating in which two‐parameter logistic and general partial credit models are employed.