Table 1.

Overview of psychometric analyses conducted.

Analysis	Description
Item-level and dimensionality analyses
Floor and ceiling effects	simple • Floor and ceiling effects were assessed by examining the proportion of respondents endorsing the lowest (floor) and highest (ceiling) possible response option for each item of the three HRQL measures. simple • An item with a floor effect > 20% or a ceiling effect > 20% in the sample was flagged (Terwee et al., 2007)
Construct validity: item-convergent and discriminant validity	simple • Item to scale correlations were calculated to explore the dimensionality and factor structure of the respective measures. Two criteria were considered: simple ∘ Item convergent validity: the item-to-scale correlation coefficient between each item and domain should be > 0.40 or higher (Cappelleri et al., 2013) simple ∘ Item discriminant validity: each item should have a higher item-to-scale correlation coefficient with its own domain than with any other domain and show small (<0.40) or negligible correlations (Cappelleri et al., 2013)
Scale-level analyses
Internal consistency	simple • Internal consistency reliability was evaluated using Cronbach’s alpha coefficient for all multi-item domains. simple • This criterion was considered to be met if the Cronbach’s alpha coefficient was ≥0.70 (Cronbach, 1951; Nunnally and Bernstein, 1994)
Known-groups validity	simple • Construct validity was assessed using the known-groups method (Hedges and Olkin, 1985) to evaluate differences in total scores among respondents who differ on health/disease related variable at baseline: simple ∘ Level of intellectual disability (two levels: <70 single ability composite WNV score and ≥70 single ability composite WNV score) simple • The criterion was considered to be met when significantly different total scores (defined as p < 0.05) were obtained between the defined subgroups (Hattie and Cooksey, 1984)
Ability to detect change	simple • t-Tests were used to examine the extent to which HRQL scores related to corresponding changes in partial-onset seizure frequency between the defined subgroups (Husted et al., 2000) simple • Patients were categorized as: simple ∘ Responders (at least a 50% reduction from baseline in seizure frequency) simple ∘ Non-responders (less than a 50% reduction from Baseline in seizure frequency)
Clinically meaningful change analyses
Distribution-based analysis	simple • Distribution-based analyses were conducted to generate change estimates, including: calculation of 0.5 of a standard deviation (SD) and standard error of measurement (SEM) (Wyrwich et al., 1999; Norman et al., 2003; de Vet et al., 2006; Revicki et al., 2008)