Table 2.

Summary statistics for selected median regression models on the basis of cubic and linear splines, and specified covariates

Variables includedModels with Log(PCR) Transformed with a Five-Knot Restricted Cubic SplineModels with Log(PCR) Transformed with a Four-Knot Linear SplineCorrelation Coefficient between Estimates from Model Pairs
ModelNo. of CoefficientsPseudo R2ModelNo. of CoefficientsPseudo R2
Spline of log(PCR) onlyC150.624L160.623>0.99
Spline of log(PCR), sex, and interactionsC2100.629L2120.628>0.99
Spline of log(PCR), sex, age, diabetes, hypertension and eGFR category, and interactionsC3400.637L3480.635>0.99
Spline of log(PCR) sex, age, diabetes, hypertension, eGFR category, laboratory location, and interactionsC4500.642L4600.641>0.99
  • The knots for the restricted cubic spline were at percentiles 5, 27.5, 50, 72.5, and 95 of log(PCR) (3.4668, 4.0625, 4.5664, 5.3992, and 7.7333, corresponding to PCR values of 32.0, 58.1, 96.2, 221, and 2283 mg/g). Knots for the linear spline were at values of log(PCR) of 3.689, 4.094, 5.521, and 6.908, corresponding to PCR values of 40, 60, 250, and 1000 mg/g. The number of coefficients includes the constant. The interactions are between the covariate and the spline terms. Pseudo R2 is the proportion of the sum of absolute deviations from the median that is explained by the model.