Bias and Precision of Continuous Norms Obtained Using Quantile Regression.

ABSTRACT: Continuous norming is an increasingly popular approach to establish norms when the performance on a test is dependent on age. However, current continuous norming methods rely on a number of assumptions that are quite restrictive and may introduce bias. In this study, quantile regression was introduced as more flexible alternative. Bias and precision of quantile regression-based norming were investigated with (age-)group as covariate, varying sample sizes and score distributions, and compared with bias and precision of two other norming methods: traditional norming and mean regression-based norming. Simulations showed the norms obtained using quantile regression to be most precise in almost all conditions. Norms were nevertheless biased when the score distributions reflected a ceiling effec

SUBMITTER: Crompvoets EAV 

PROVIDER: S-EPMC8392776 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature