Home E Publications E A comparison of methods to address item non-response when testing for differential item functioning in multidimensional patient-reported outcome measures

A comparison of methods to address item non-response when testing for differential item functioning in multidimensional patient-reported outcome measures

Authors:

Olawale F. Ayilara, Tolulope T. Sajobi, Ruth Barclay, Eric Bohm, Mohammad Jafari Jozani & Lisa M. Lix

Date:

2022
Journal
Quality of Life Research

Abstract:

Item non-response (i.e., missing data) may mask the detection of differential item functioning (DIF) in patient-reported outcome measures or result in biased DIF estimates. Non-response can be challenging to address in ordinal data. We investigated an unsupervised machine-learning method for ordinal item-level imputation and compared it with commonly-used item non-response methods when testing for DIF. The NNMF method demonstrated comparable performance to commonly-used non-response methods. This computationally-efficient method represents a promising approach to address item-level non-response when testing for DIF.