On Estimation and Tests of Time-Varying Effects in the Proportional Hazards Model

DOI10.1111/j.1467-9469.2004.00372.xzbMath1053.62111OpenAlexW2143273269MaRDI QIDQ4828226

Torben Martinussen, Thomas H. Scheike

Publication date: 24 November 2004

Published in: Scandinavian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-9469.2004.00372.x

zbMATH Keywords

kernel estimatebaseline hazardindependence of time test

Mathematics Subject Classification ID

Density estimation (62G07) Applications of statistics to biology and medical sciences; meta analysis (62P10) Estimation in survival analysis and censored data (62N02) Testing in survival analysis and censored data (62N03)

Related Items (16)

Estimability in Cox models ⋮ Data-driven smooth tests of the proportional hazards assumption ⋮ Marginal Regression Model with Time-Varying Coefficients for Panel Data ⋮ Estimating Cumulative Treatment Effects in the Presence of Nonproportional Hazards ⋮ Bootstrap and permutation rank tests for proportional hazards under right censoring ⋮ Comparison of procedures to assess non‐linear and time‐varying effects in multivariable models for survival data ⋮ Reduced rank hazard regression with fixed and time‐varying effects of the covariates ⋮ Estimation in hazard regression models under ordered departures from proportionality ⋮ Dynamic Prediction by Landmarking in Event History Analysis ⋮ Partial orders with respect to continuous covariates and tests for the proportional hazards model ⋮ The wild bootstrap for multivariate Nelson-Aalen estimators ⋮ Estimating Haplotype Effects for Survival Data ⋮ Identifying Nonproportional Covariates in the Cox Model ⋮ Time-Dependent Predictive Accuracy in the Presence of Competing Risks ⋮ Regression analysis of multivariate recurrent event data with time-varying covariate effects ⋮ Extensions and Applications of the Cox‐Aalen Survival Model

Cites Work

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• Time-dependent coefficients in a Cox-type regression model
• The additive nonparametric and semiparametric Aalen model as the rate function for a counting process
• Efficient Estimation of Fixed and Time‐varying Covariate Effects in Multiplicative Intensity Models
• Semiparametric Regression for the Mean and Rate Functions of Recurrent Events
• Statistical models based on counting processes

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