Package: sportsfeatures 0.3.0

Overview | Why sportsfeatures? | Core Premise | Framework Structure | Vignette Research Pathway | Pillar 1: Variance Structure & Hierarchical Non‑Constant Spread | Baseline Illustration | Table 1.1: Simple Linear Regression Model Coefficients | Hierarchical Variance Decomposition | Modelling Implications | Pillar 2: Missing Not At Random (MNAR) & MICE Imputation | Wearable Device Dropout Mechanics | Imputation Workflow | Diagnostic Verification: Iterative Chain Convergence | Interpretation | Pillar 3: Derived Variables & Physiological Constructs | Table 1.2 summarises the principal derived variables within the framework, along with their hierarchical classification and intended role in modelling. | Notes on Multilevel Classification | What Next? From Framework to Analytical Discovery | Concluding Remarks