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Incorporating time‐dependent covariates into tree‐structured survival analysis (TSSA) may result in more accurate prognostic models than if only baseline values are used. Available time‐dependent TSSA methods exhaustively test every binary split on every covariate; however, this approach may result in selection bias toward covariates with more observed values. We present a method that uses unbiased...
Missing covariate data present a challenge to tree‐structured methodology due to the fact that a single tree model, as opposed to an estimated parameter value, may be desired for use in a clinical setting. To address this problem, we suggest a multiple imputation algorithm that adds draws of stochastic error to a tree‐based single imputation method presented by Conversano and Siciliano (Technical Report...
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