A multilevel item response theory model was investigated for longitudinal vision-related quality-of-life data

Abstract 

Objective

To investigate how a multilevel item response theory (IRT) model for longitudinal dependent data could provide average and individual quality-of-life outcomes of low-vision rehabilitation.

Study Design and Setting

In a nonrandomized longitudinal design, visually impaired older patients (n=296) were referred to multidisciplinary rehabilitation or to an optometric service. The five-dimensional Low Vision Quality of Life Questionnaire was administered at four time points. The IRT model was characterized by the graded response model for rating scales. Covariates were added to the model, mainly to correct for missing data. The invariance assumption across time points was investigated.

Results

Average and individual rehabilitation effects were estimated. For multidisciplinary rehabilitation, significant average deterioration was seen on three dimensions after 4.4 years. Many individuals in the optometric service group significantly improved on the “reading small print” dimension (18.5%); in both groups, many individuals significantly deteriorated on “visual (motor) skills” (22.2–30.0%). Invariance across time points could be assumed for all dimensions, except for “adjustment.” Gender, education, visual acuity, and health status were significantly associated with the outcome.

Conclusion

We present how a multilevel IRT model can be applied to describe longitudinal dependent vision-related quality-of-life data, while focusing on average and individual effects.

Keywords: IRT, Multilevel analysis, Graded response model, Rating scale model, Missing data, Vision-related quality of life