CMStatistics 2017: Start Registration
View Submission - CMStatistics
Title: Combining confidence intervals: Uncertainty in normed test scores due to test unreliability and sampling variability Authors:  Lieke Voncken - University of Groningen (Netherlands) [presenting]
Casper Albers - University of Groningen (Netherlands)
Marieke Timmerman - University of Groningen (Netherlands)
Abstract: Test publishers usually provide confidence intervals for normed test scores that reflect the uncertainty due to the unreliability of the tests. The uncertainty due to sampling variability in the norming phase is ignored in practice. To enable a fair positioning of the person under study relative to the norm population, it is important to account for both sources of uncertainty. A flexible method is proposed that combines both types of uncertainty in one confidence interval. This method is applicable in continuous norming and is very flexible in terms of the score distribution, using the Generalized Additive Models for Location, Scale, and Shape (GAMLSS) framework. The performance of the method is assessed in a simulation study. The findings are discussed and the method is illustrated with real norming data.