Cataract Symptom Score Questionnaire: Rasch Revalidation

Abstract

The CSS is unable to discriminate people with cataract. This problem could be fixed by adding additional questions, but a superior approach may be to create an item bank of cataract symptoms questions, including those of the CSS, and utilize computer-adaptive testing for measurement.

Improvements in visual ability with first-eye, second-eye, and bilateral cataract surgery measured with the Visual Symptoms and Quality of Life Questionnaire

“…Except for the Catquest-9SF, 35 poor targeting has been a characteristic feature of most questionnaires developed for first-eye surgery patients. [12][13][14]16,17,44,45,[47][48][49][50] Two items, 7 and 13, showed notable differential item functioning between after first-eye and before second-eye cataract surgery. However, it is difficult to dig further in the differential item functioning issue and premature to draw any conclusion about the performance of these 2 items considering the small number of cases available for differential item functioning analysis.…”

Vision and Quality of Life Index: Validation of the Indian Version Using Rasch Analysis

“…For a well-targeted instrument, the mean item difficulty (this usually is set at zero) would match mean person ability of the population; a difference between the means of >1.0 logits indicates notable mistargeting. 41 Finally, we assessed differential item functioning or DIF (indicator of the presence of any systematic differences between the various item difficulty estimates across subgroups of participants). 42 We selected the variables for DIF analysis a priori and these included age (<43 vs. ‡43 years; median age, 43), sex, number of years of education (<10 vs. ‡10 years), work status (working versus not working), systemic comorbidity (present versus absent), and VI group (low vision versus blind).…”

Assessment of the Impact of Keratoconus on Vision-Related Quality of Life

“…This approach has been described previously. 37,38 Rasch analysis is an iterative procedure that estimates interval measurement from ordinal data and the unit is logits (log-odd units). [38][39][40] For our study, a negative item logit indicates a more difficult item and a negative logit value for a participant indicates that the he/she possesses a higher level of the assessed latent construct (VRQoL); that is, better VRQoL.…”

“…(4) Targeting was the extent to which the items match participant's VRQoL, and was inspected using the person-item map; >1.0 logits indicates notable mistargeting. 37 (5) Unidimensionality was defined as the extent to which all the items measure a single underlying construct (VRQoL in the case of IVI) assessed by principal components analysis (PCA). The rationale for this is that after the ''Rasch factor'' has been extracted (in an attempt to account for all variation in the data) only standardized residuals equivalent to random noise should remain.…”