Statistics
REGRESSION, AIDS, REGRESSIONS, DELETION
Statistical analyses were performed using STATA (StataCorp. 2019. Stata Statistical Software: Release 17. College Station, TX: StataCorp LLC). Agreement was assessed with Cohen’s Kappa, and was rated as > 0.9 almost perfect agreement, 0.8–0.9 strong, 0.6–0.79 moderate, 0.4–0.59 weak, 0.21–0.39 minimal, and ≤ 0.2 no agreement.Associations with continuous frailty scores were analysed using linear regression, having satisfied the linear assumption via visual comparison of observed versus Lowess fit lines on scatter plot and augmented component plus residual plots. Robust standard errors were specified to account for heteroscedasticity. Multicollinearity was excluded on all analyses by variance inflation factor < 10. Odds ratios for frailty were obtained by logistic regression.Linear and logistic regressions were performed both unadjusted and adjusted for a priori covariables chosen for proven or suspected association with frailty. These were introduced in a stepwise manner; Model 1 included age, ethnicity, gender, education level, IMD quintile, self-reported social support (Yes/No), and haemodialysis vintage. Model 2 added to these self-reported health today (Euroqol 5D Visual Analogue Scale) [As statistical significance was lost for many frailty associations with stepwise addition of covariables, a sensitivity analysis was performed whereby the order of addition of covariables was reversed to explore the likelihood of type II error. Therefore, Model A included self-reported slow walking speed, and use of walking aids. Model B added self-reported health today [Missing IMD quintiles were handled via a dummy variable. All other missing data were handled via listwise deletion, as < 1% of other data were missing. A 